{
  "source_file": "0930",
  "source_platform": "Medium",
  "author": "Cai Parry-Jones",
  "title_listed": "Stop Being Data-Driven",
  "keywords": "",
  "domain": "数据处理",
  "content_type": "深度技术解析",
  "is_paid_flag": "否",
  "url": "https://towardsdatascience.com/stop-being-data-driven-583b5e7abe7b/",
  "publish_date": "2024-08-30",
  "corpus_stage": "",
  "notes": "",
  "id": "31fae598d8a6",
  "collected_at": "2026-10-02T05:26:28",
  "title": "Stop Being Data-Driven | Towards Data Science",
  "body_markdown": "![Revisit consent button](../images/body-df29beacd7496220cc94.svg)\nWe value your privacy\nWe use cookies to enhance your browsing experience, serve personalised ads or content, and analyse our traffic. By clicking \"Accept All\", you consent to our use of cookies.\nCustomise Reject All Accept All\nCustomise Consent Preferences ![](../images/body-2159bb67f3de8ad870eb.svg)\nWe use cookies to help you navigate efficiently and perform certain functions. You will find detailed information about all cookies under each consent category below.\nThe cookies that are categorised as \"Necessary\" are stored on your browser as they are essential for enabling the basic functionalities of the site. ... Show more\nNecessaryAlways Active\nNecessary cookies are required to enable the basic features of this site, such as providing secure log-in or adjusting your consent preferences. These cookies do not store any personally identifiable data.\n  * Cookie\nBCTempID\n  * Duration\n10 minutes\n  * Description\nNo description available.\n\n\n  * Cookie\n__cf_bm\n  * Duration\n1 hour\n  * Description\nThis cookie, set by Cloudflare, is used to support Cloudflare Bot Management. \n\n\n  * Cookie\nAWSALBCORS\n  * Duration\n7 days\n  * Description\nAmazon Web Services set this cookie for load balancing.\n\n\n  * Cookie\n_cfuvid\n  * Duration\nsession\n  * Description\nCloudflare sets this cookie to track users across sessions to optimize user experience by maintaining session consistency and providing personalized services\n\n\n  * Cookie\nli_gc\n  * Duration\n6 months\n  * Description\nLinkedin set this cookie for storing visitor's consent regarding using cookies for non-essential purposes.\n\n\n  * Cookie\n__hssrc\n  * Duration\nsession\n  * Description\nThis cookie is set by Hubspot whenever it changes the session cookie. The __hssrc cookie set to 1 indicates that the user has restarted the browser, and if the cookie does not exist, it is assumed to be a new session.\n\n\n  * Cookie\n__hssc\n  * Duration\n1 hour\n  * Description\nHubSpot sets this cookie to keep track of sessions and to determine if HubSpot should increment the session number and timestamps in the __hstc cookie.\n\n\n  * Cookie\nwpEmojiSettingsSupports\n  * Duration\nsession\n  * Description\nWordPress sets this cookie when a user interacts with emojis on a WordPress site. It helps determine if the user's browser can display emojis properly.\n\n\n  * Cookie\nBCSessionID\n  * Duration\n1 year 1 month 4 days\n  * Description\nBlueconic sets this cookie as a unique identifier for the BlueConic profile.\n\n\n  * Cookie\n_octo\n  * Duration\n1 year\n  * Description\nNo description available.\n\n\n  * Cookie\nlogged_in\n  * Duration\n1 year\n  * Description\nNo description available.\n\n\n  * Cookie\n__Secure-YEC\n  * Duration\npast\n  * Description\nYouTube sets this cookie to stores the user's video player preferences using embedded YouTube video\n\n\n  * Cookie\n__eoi\n  * Duration\n6 months\n  * Description\nDescription is currently not available.\n\n\n  * Cookie\nAWSALBTGCORS\n  * Duration\n7 days\n  * Description\nNo description available.\n\n\n  * Cookie\nlogin-status-p\n  * Duration\npast\n  * Description\nDescription is currently not available.\n\n\n  * Cookie\nAWSALBTG\n  * Duration\n7 days\n  * Description\nNo description available.\n\n\n  * Cookie\ncsrf_token\n  * Duration\nsession\n  * Description\nNo description available.\n\n\n  * Cookie\ntoken_v2\n  * Duration\n1 day\n  * Description\nDescription is currently not available.\n\n\n  * Cookie\nD\n  * Duration\n1 year\n  * Description\nDescription is currently not available.\n\n\n  * Cookie\nPHPSESSID\n  * Duration\nsession\n  * Description\nThis cookie is native to PHP applications. The cookie stores and identifies a user's unique session ID to manage user sessions on the website. The cookie is a session cookie and will be deleted when all the browser windows are closed.\n\n\n  * Cookie\nVISITOR_PRIVACY_METADATA\n  * Duration\n6 months\n  * Description\nYouTube sets this cookie to store the user's cookie consent state for the current domain. \n\n\n  * Cookie\ncookietest\n  * Duration\nsession\n  * Description\nThe cookietest cookie is typically used to determine whether the user's browser accepts cookies, essential for website functionality and user experience.\n\n\n  * Cookie\n__Host-airtable-session\n  * Duration\n1 year\n  * Description\nThis cookie is used to enable us to integrate the services of Airtable.\n\n\n  * Cookie\n__Host-airtable-session.sig\n  * Duration\n1 year\n  * Description\nThis cookie is used to enable us to integrate the services of Airtable.\n\n\n  * Cookie\nm\n  * Duration\n1 year 1 month 4 days\n  * Description\nStripe sets this cookie for fraud prevention purposes. It identifies the device used to access the website, allowing the website to be formatted accordingly.\n\n\n  * Cookie\nBIGipServer*\n  * Duration\nsession\n  * Description\nMarketo sets this cookie to collect information about the user's online activity and build a profile about their interests to provide advertisements relevant to the user. \n\n\n  * Cookie\n__cfruid\n  * Duration\nsession\n  * Description\nCloudflare sets this cookie to identify trusted web traffic.\n\n\n  * Cookie\n_GRECAPTCHA\n  * Duration\n6 months\n  * Description\nGoogle Recaptcha service sets this cookie to identify bots to protect the website against malicious spam attacks.\n\n\n  * Cookie\n__Secure-YNID\n  * Duration\n6 months\n  * Description\nGoogle cookie used to protect user security and prevent fraud, especially during the login process.\n\n\n  * Cookie\ncookieyes-consent\n  * Duration\n1 year\n  * Description\nCookieYes sets this cookie to remember users' consent preferences so that their preferences are respected on subsequent visits to this site. It does not collect or store any personal information about the site visitors.\n\n\nFunctional\nFunctional cookies help perform certain functionalities like sharing the content of the website on social media platforms, collecting feedback, and other third-party features.\n  * Cookie\nlidc\n  * Duration\n1 day\n  * Description\nLinkedIn sets the lidc cookie to facilitate data center selection.\n\n\n  * Cookie\nbrw\n  * Duration\n1 year\n  * Description\nNo description available.\n\n\n  * Cookie\nbrwConsent\n  * Duration\n5 minutes\n  * Description\nDescription is currently not available.\n\n\n  * Cookie\nWMF-Uniq\n  * Duration\n1 year\n  * Description\nDescription is currently not available.\n\n\n  * Cookie\nloom_anon_comment\n  * Duration\n1 year\n  * Description\nNo description available.\n\n\n  * Cookie\nloom_referral_video\n  * Duration\nsession\n  * Description\nDescription is currently not available.\n\n\n  * Cookie\nVISITOR_INFO1_LIVE\n  * Duration\n6 months\n  * Description\nA cookie set by YouTube to measure bandwidth that determines whether the user gets the new or old player interface.\n\n\n  * Cookie\nyt-remote-connected-devices\n  * Duration\nNever Expires\n  * Description\nYouTube sets this cookie to store the user's video preferences using embedded YouTube videos.\n\n\n  * Cookie\nytidb::LAST_RESULT_ENTRY_KEY\n  * Duration\nNever Expires\n  * Description\nThe cookie ytidb::LAST_RESULT_ENTRY_KEY is used by YouTube to store the last search result entry that was clicked by the user. This information is used to improve the user experience by providing more relevant search results in the future.\n\n\n  * Cookie\nyt-remote-device-id\n  * Duration\nNever Expires\n  * Description\nYouTube sets this cookie to store the user's video preferences using embedded YouTube videos.\n\n\n  * Cookie\nyt-remote-session-name\n  * Duration\nsession\n  * Description\nThe yt-remote-session-name cookie is used by YouTube to store the user's video player preferences using embedded YouTube video.\n\n\n  * Cookie\nyt-remote-fast-check-period\n  * Duration\nsession\n  * Description\nThe yt-remote-fast-check-period cookie is used by YouTube to store the user's video player preferences for embedded YouTube videos.\n\n\n  * Cookie\nyt-remote-session-app\n  * Duration\nsession\n  * Description\nThe yt-remote-session-app cookie is used by YouTube to store user preferences and information about the interface of the embedded YouTube video player.\n\n\n  * Cookie\nyt-remote-cast-available\n  * Duration\nsession\n  * Description\nThe yt-remote-cast-available cookie is used to store the user's preferences regarding whether casting is available on their YouTube video player.\n\n\n  * Cookie\nyt-remote-cast-installed\n  * Duration\nsession\n  * Description\nThe yt-remote-cast-installed cookie is used to store the user's video player preferences using embedded YouTube video.\n\n\n  * Cookie\ncp_session\n  * Duration\n3 months\n  * Description\nCodepen sets this cookie for Help systems found in the website.\n\n\n  * Cookie\nloid\n  * Duration\n1 year 1 month 4 days\n  * Description\nThis cookie is set by the Reddit. The cookie enables the sharing of content from the website onto the social media platform.\n\n\nAnalytics\nAnalytical cookies are used to understand how visitors interact with the website. These cookies help provide information on metrics such as the number of visitors, bounce rate, traffic source, etc.\n  * Cookie\n__hstc\n  * Duration\n6 months\n  * Description\nHubspot set this main cookie for tracking visitors. It contains the domain, initial timestamp (first visit), last timestamp (last visit), current timestamp (this visit), and session number (increments for each subsequent session).\n\n\n  * Cookie\nhubspotutk\n  * Duration\n6 months\n  * Description\nHubSpot sets this cookie to keep track of the visitors to the website. This cookie is passed to HubSpot on form submission and used when deduplicating contacts.\n\n\n  * Cookie\n_ga\n  * Duration\n1 year 1 month 4 days\n  * Description\nGoogle Analytics sets this cookie to calculate visitor, session and campaign data and track site usage for the site's analytics report. The cookie stores information anonymously and assigns a randomly generated number to recognise unique visitors.\n\n\n  * Cookie\n_ga_*\n  * Duration\n1 year 1 month 4 days\n  * Description\nGoogle Analytics sets this cookie to store and count page views.\n\n\n  * Cookie\n__Host-psifi.analyticsTrace\n  * Duration\n6 hours\n  * Description\nDescription is currently not available.\n\n\n  * Cookie\n__Host-psifi.analyticsTraceV2\n  * Duration\n6 hours\n  * Description\nDescription is currently not available.\n\n\n  * Cookie\n_gh_sess\n  * Duration\nsession\n  * Description\nGitHub sets this cookie for temporary application and framework state between pages like what step the user is on in a multiple step form.\n\n\n  * Cookie\nYSC\n  * Duration\nsession\n  * Description\nYSC cookie is set by Youtube and is used to track the views of embedded videos on Youtube pages.\n\n\n  * Cookie\najs_anonymous_id\n  * Duration\n1 year\n  * Description\nThis cookie is set by Segment to count the number of people who visit a certain site by tracking if they have visited before.\n\n\n  * Cookie\nvuid\n  * Duration\n1 year 1 month 4 days\n  * Description\nVimeo installs this cookie to collect tracking information by setting a unique ID to embed videos on the website. \n\n\nPerformance\nPerformance cookies are used to understand and analyse the key performance indexes of the website which helps in delivering a better user experience for the visitors.\n  * Cookie\nAWSALB\n  * Duration\n7 days\n  * Description\nAWSALB is an application load balancer cookie set by Amazon Web Services to map the session to the target.\n\n\n  * Cookie\nacq\n  * Duration\npast\n  * Description\nDescription is currently not available.\n\n\n  * Cookie\nacq.sig\n  * Duration\npast\n  * Description\nDescription is currently not available.\n\n\n  * Cookie\nptc\n  * Duration\n2 years\n  * Description\nNo description available.\n\n\nAdvertisement\nAdvertisement cookies are used to provide visitors with customised advertisements based on the pages you visited previously and to analyse the effectiveness of the ad campaigns.\n  * Cookie\nmuc_ads\n  * Duration\n1 year 1 month 4 days\n  * Description\nTwitter sets this cookie to collect user behaviour and interaction data to optimize the website.\n\n\n  * Cookie\nguest_id_marketing\n  * Duration\n1 year 1 month 4 days\n  * Description\nTwitter sets this cookie to identify and track the website visitor.\n\n\n  * Cookie\nguest_id_ads\n  * Duration\n1 year 1 month 4 days\n  * Description\nTwitter sets this cookie to identify and track the website visitor.\n\n\n  * Cookie\npersonalization_id\n  * Duration\n1 year 1 month 4 days\n  * Description\nTwitter sets this cookie to integrate and share features for social media and also store information about how the user uses the website, for tracking and targeting.\n\n\n  * Cookie\nguest_id\n  * Duration\n1 year 1 month 4 days\n  * Description\nTwitter sets this cookie to identify and track the website visitor. It registers if a user is signed in to the Twitter platform and collects information about ad preferences.\n\n\n  * Cookie\nbcookie\n  * Duration\n1 year\n  * Description\nLinkedIn sets this cookie from LinkedIn share buttons and ad tags to recognize browser IDs.\n\n\n  * Cookie\n__Secure-ROLLOUT_TOKEN\n  * Duration\n6 months\n  * Description\nYouTube sets this cookie to manage feature rollout and experimentation. It helps Google control which new features or interface changes are shown to users as part of testing and staged rollouts, ensuring consistent experience for a given user during an experiment.\n\n\n  * Cookie\nyt.innertube::nextId\n  * Duration\nNever Expires\n  * Description\nYouTube sets this cookie to register a unique ID to store data on what videos from YouTube the user has seen.\n\n\n  * Cookie\nyt.innertube::requests\n  * Duration\nNever Expires\n  * Description\nYouTube sets this cookie to register a unique ID to store data on what videos from YouTube the user has seen.\n\n\n  * Cookie\nsession_tracker\n  * Duration\nsession\n  * Description\nThis cookie is set by the Reddit. This cookie is used to identify trusted web traffic. It also helps in adverstising on the website.\n\n\n  * Cookie\nedgebucket\n  * Duration\nsession\n  * Description\nReddit sets this cookie to save the information about a log-on Reddit user, for the purpose of advertisement recommendations and updating the content.\n\n\n  * Cookie\ndid\n  * Duration\n1 year\n  * Description\nArbor sets this cookie to show targeted ads to site visitors.This cookie expires after 2 months or 1 year.\n\n\nUncategorised\nOther uncategorised cookies are those that are being analysed and have not been classified into a category as yet.\nNo cookies to display.\nReject All Save My Preferences Accept All\nToggle Search[](https://towardsdatascience.com/)Toggle Mobile Navigation\n[](https://towardsdatascience.com/)\nPublish AI, ML & data-science insights to a global community of data professionals.\nSign in[Submit an Article](https://write.insightmediagroup.io)\n[Latest](https://towardsdatascience.com/latest/)[Editor's Picks](https://towardsdatascience.com/tag/editors-pick/)[Newsletter](https://towardsdatascience.com/tag/the-variable/)[ShipAI](https://towardsdatascience.com/shipai/)\n* * *\n[Write For TDS](https://towardsdatascience.com/submissions/)\n[LinkedIn](https://www.linkedin.com/company/towards-data-science/)[X](https://x.com/TDataScience)Toggle Search\n[Data Science](https://towardsdatascience.com/category/data-science/)\n# Stop Being Data-Driven\nWhy we are fooled by data and how to stop it\n[Cai Parry-Jones](https://towardsdatascience.com/author/caiparryjones96/)\nAugust 29, 202411 min read\n![source: unsplash.com](../images/000.jpg)\nsource: [unsplash.com](https://unsplash.com/)\nOften, when making decisions based on data, we feel as if we have made a more intelligent, accurate choice. The reality is a little different. From [real estate purchases](https://www.fullstackeconomics.com/p/why-zillow-is-like-my-bad-fantasy-football-team) to [dietary choices](https://www.scientificamerican.com/article/quack-cancer-diets-endanger-people-stick-to-science-backed-medicine/) to [corporate board selections](https://www.spectator.co.uk/article/is-diversity-actually-good-for-business/), data can be an amazing catalyst to help make the worst decisions.\nImagine data as that brilliant yet unpredictable friend of yours. One moment they're a genius, the next a complete mess. Would you hand them the keys to your beloved Ford Focus? Or would you politely insist they take the passenger seat?\nThis article explores why data belongs firmly in the passenger seat, not behind the wheel. It will examine real-world examples where data-driven decisions could have steered us off course and into the cliff of misinformation. Fortunately, this article also gives actionable, easy-to-use advice on how to avoid such scenarios by following a four-step ladder to assess the quality of data-driven insights:\n  1. Evaluating the data source,\n  2. Considering the bias of the data presenter,\n  3. Recognising the bias of the data reader,\n  4. Identifying any logical missteps between the data and the insight.\n\n\nBy the end of this journey, you'll be better prepared to navigate the road of decision-making, while keeping your unpredictable friend safely buckled in the passenger seat.\nLearn this step by step with the interactive [AI and Data Scientist](https://roadmap.sh/ai-data-scientist) roadmap.\n## TL;DR\n  * Always question the source of the data. If the source isn't credible or isn't provided, don't be shy in rejecting the entire analysis.\n  * Don't hesitate to fact-check claims, especially when they seem counterintuitive.\n  * Be aware of the data presenters bias. Ask yourself if they'd present the same analysis if it led to the opposite conclusion.\n  * Be aware of confirmation bias. Ask yourself if you'd accept the same analysis if it led to the opposite conclusion.\n  * Consider whether the analysis makes logical sense. Just because two things are correlated doesn't mean one causes the other.\n  * Recognise that data interpretation often involves assumptions and leaps in logic. It's crucial to identify and evaluate these leaps using your own judgment.\n\n\n## Question One - Where did the data come from?\nHere is an excerpt from an article published in The Spectator, titled: '[The unfashionable truth about the riots](https://www.spectator.co.uk/article/the-unfashionable-truth-about-the-riots/)'. Its subject is the 2024 anti-immigration riots in the UK.\n> ...I decided to do some checking on the employment stats for some of the northern towns that have seen the worst rioting in the past week. I also checked the 2011 statistics and then compared the two. I should warn you in advance that if you're easily depressed, you should look away now.\n> Back in 2011, the proportion on out-of-work benefits (including incapacity benefit) in Sunderland was 18 per cent; today it is 19 per cent. In 2011 the unemployment figure in Rotherham was 16 per cent; today it is 18 per cent. In Hartlepool, it was 21 per cent; today, 23 per cent.\n>   * [The unfashionable truth about the riots](https://www.spectator.co.uk/article/the-unfashionable-truth-about-the-riots/), The Spectator\n> \n\nSo, where did this data come from?\nIn the example, all we have is \"the employment stats\"... What the heck does that mean? In the UK there isn't a centralised place for employment statistics, so it's far from obvious what data the author is referring to. You might be content with dismissing the data and thus dismissing the rest of the article, since its premise is based on this data. However, I'm a try-hard, so I put on my best Sherlock Holmes hat and set about finding the un-cited data.\nSadly, I am not Sherlock Holmes. Despite considerable online sleuthing, I couldn't find any data that matched the article's. I did, however, find other \"employment stats\". Specifically the Office of National Statistics (ONS)'s [measure of unemployment](https://www.ons.gov.uk/employmentandlabourmarket/peoplenotinwork/unemployment) by region. It paints a very different picture. In fact the polar opposite picture! Of the three areas the article highlights as having reduced in employment since 2011, the ONS in fact finds they all increased!* I'm afraid the only unfashionable truth illuminated by this article is the degradation of news media. (Or was it always like this?)\n_*Data links: [Sunderland](https://www.nomisweb.co.uk/reports/lmp/la/1946157068/subreports/ea_time_series/report.aspx), [Rotherham](https://www.nomisweb.co.uk/reports/lmp/la/1946157122/subreports/ea_time_series/report.aspx), and [Hartlepool](https://www.nomisweb.co.uk/reports/lmp/la/1946157059/subreports/ea_time_series/report.aspx) employment stats._\n## Question Two - What if the opposite result were true?\n> ...Using laboratory and field experiments, we find that signing before–rather than after–the opportunity to cheat makes ethics salient when they are needed most and significantly reduces dishonesty.\n>   * [Signing at the beginning makes ethics salient and decreases dishonest self-reports in comparison to signing at the end](https://sci-hub.se/10.1073/pnas.1209746109), Lisa L. Shu et al.\n> \n\nThis quote comes from the abstract of a highly influential research paper in Behavioural Science. In case you didn't quite understand the quote, since it is written in the classic academic obfuscation style, the quote is saying that signing your name on the top of a document makes you less likely to lie about the document than if you had signed on the bottom.\nThe data came from a collection of researchers based in highly regarded universities, most notably Francesca Gino who was a professor at Harvard Business School at the time of publication. For me, this passes our first question about the data ('Where did the data come from?').\nNext we need to ask: 'Would the data be presented if the opposite result were true?' To answer this we first need to understand a little about the people and/or institutes presenting the data. In this case it is a group of Behavioural Science academics. Academia is a cut-throat industry, with an exceptionally [high failure rate](https://www.youtube.com/watch?v=XAOs-frRfa4&t=285s). Therefore, it is critical for academics to be considered 'successful' as early as possible to avoid being culled. The key factor to determine an academic's success is, unsurprisingly, their work. But how do you measure the quality of their work? A common method is [citation count](https://www.stjude.org/research/progress/2020/the-benefits-of-being-highly-cited.html#:~:text=The%20more%20citations%20you%20have,based%20on%20their%20impact%20factor.), that is the number of times an academic's work is mentioned in the work of other academics.\nThe issue with this is you are far more likely to to be cited if you have an unexpected/interesting result in your paper. Going back to the original quote, do you think a result where there was no difference in honesty between the group who signed at the top vs the bottom of a document would have been nearly as influential? No, because that would have been the expectation. The conclusion is that there is a strong incentive for academics to generate unexpected/interesting results. Therefore, in our example, we should understand that there is a strong bias for the authors to claim a (significant) difference in honesty between the two groups.\nThis sort of bias is so strong that it has led the [majority of scientific research to be unreproducible by fellow academics](https://www.bbc.co.uk/news/science-environment-39054778). Unreproducible means an academic writes a research paper that copies another academic's research paper's method/experiment, but ends up with significantly different results to the original paper. Turning once more to our case study as an example, following the impactful success of the research paper, a number of other studies attempted to run the same or similar experiment. [All results](https://www.pnas.org/doi/10.1073/pnas.1911695117) of the experiments found no correlation between honesty and location of document signature. It turned out the original paper's finding was very likely the result of [data fraud](https://datacolada.org/109). As were a [number of other influential papers](https://www.youtube.com/watch?v=yNK4nXWA_s8) co-authored by the prestigious Harvard professor, Francesca Gino.\nThis sort of skin-in-the-game bias isn't only found in academia. From [tech vendors posting their latest performances vs competitors](https://www.starburst.io/blog/lie-5-vendor-benchmarks-measure-real-world-performance/), to investment banks presenting to prospective clients that they are no. 1 in the league tables*, bias is rife. And it isn't only other people you should be concerned about. The strongest bias of all is most likely you—yes, YOU. Commonly referred to as confirmation bias, it is the tendency to search for, interpret, favour, and recall information in a way that confirms or supports your prior beliefs.\nEver wondered why such a mass of people could be so stupid on so many political topics? Sadly, it is more likely a result of [your own confirmation bias](https://danielnations.medium.com/why-do-republicans-and-democrats-let-other-people-do-their-thinking-dc6d208945e4) than the collective dim-wittedness of millions of people.\nIf you want to avoid the pitfalls of your own biases, as well as the biases of the data presenter, you not only need to ask: 'Would the data be presented if the opposite result were true?' But also: 'Would I consider the data presented if the opposite result were true?' It may be a tough pill to swallow, but overcoming your own bias may enlighten you more than all the research in the world.\n_*_[_May Contain Lies_](https://maycontainlies.com/) _, Alex Edmans. Page 130._\n## Question Three - Is there a flaw with the leap from data to insight?\n> For most university graduates, having a degree pays.\n> Over the course of a lifetime, estimates suggest women can expect to earn about £250,000 more if they have a degree, while the figure is roughly £170,000 for men.\n>   * [The degrees that make you rich... and the ones that don't](https://www.bbc.co.uk/news/education-41693230), BBC News\n> \n\nThis quote comes from the news department of the prestigious British Broadcasting Corporation (BBC). Specifically, their article titled: '[The degrees that make you rich... and the ones that don't](https://www.bbc.co.uk/news/education-41693230)'. First things first, is there a reliable data source?\n![The source. BBC News, The degrees that make you rich... and the ones that don't](../images/001.png)\nThe source. BBC News, [The degrees that make you rich... and the ones that don't](https://www.bbc.co.uk/news/education-41693230)\nGreat news, the answer is (probably*) yes! The article cites their data from another prestigious organisation, the Institute of Fiscal Studies. You may want to delve deeper into the exact report of the data source, but for a surface-level analysis, I'm happy with where this raw data has come from.\nSecond we want to ask ourselves, 'would this information be presented if the opposite result was true?' Given the BBC has (to my knowledge) no reason to support higher education institutions, it's fair to assume that the BBC would have published an article highlighting no financial benefits to studying at university if the data suggested it.\nHowever, unfortunately, we still can't trust the BBC's findings just yet. We have one final important question to ask: 'Does the analysis make sense?' After looking at the [article](https://www.bbc.co.uk/news/education-41693230)'s chart on average earnings by subject, have a go at answering the following question before moving on to the next paragraph: 'Given people with Medicine degrees earn more than the average degree, does it make sense to assume that the Medicine degree was the cause of the higher salary?'\nMy answer: Medicine degrees are necessary to become qualified doctors, and doctors generally earn a high income. This supports the idea that a Medicine degree is the specific reason for average higher future earnings. On the other hand, you don't just need to pick Medicine, you also need to _be_ picked for Medicine. Given the average A-level results for a UK Medicine graduate is an outstanding [AAA](https://www.medify.co.uk/blog/a-level-requirements#:~:text=Most%20medical%20schools%20require%20AAA,each%20medical%20school%20requires%20below.&text=A*AA%20\\(AAA%20considered%20if,biology%20and%20EPQ%20grade%20B\\)), you could argue the reason for the high average salaries is because the average Medicine student is exceptionally cognitively capable (in academia at least), which has nothing to do with whether they actually chose Medicine as a degree or not.\nWhat about the degree with the second highest average salary, Economics? Unlike Medicine, you don't strictly need an Economics degree to qualify for any specific high-paying jobs. I'd argue an Economics degree is much less likely a direct factor in increasing a graduate's future salary. For example, someone who is genuinely interested in money at school will be more likely to base their career decisions on what pays more. That same person may also be more likely to pick Economics at university.** If that's true, then pushing someone who is not interested in money to study Economics may not benefit their future career or financial prospects as much as the article is implying.\nSimilarly, someone who earns a university degree in general may be little to no better off than if they hadn't gone to university at all. It may simply be a side effect. For example, in the UK [children with wealthy parents are significantly more likely to attend university](https://commonslibrary.parliament.uk/research-briefings/cbp-9195/#:~:text=Pupils%20eligible%20for%20free%20school,second%20year%20in%20higher%20education.). The wealth of their parents may also have an impact on the child's high-paying job prospects; for example, they might provide invaluable knowledge to their children on how to interview, climb the greasy corporate ladder, and/or network. Given this thought process, the article's finding that \"For most university graduates, having a degree pays\" is, at the very least, not a proven fact, and should not be treated as such.\nDeciding what 'makes sense' is subjective; for example, you may not have been convinced by my arguments above. However, it's important to recognise the leaps in assumptions people make from data to insights, and to do your own 'makes sense' assessment before accepting them.\n_*It's important to acknowledge the limitations of time we have on the depth of our investigation. For very serious things you will want to go deeper, but as a pragmatist, it isn't possible for every data analysis we see._\n_**You may be thinking: 'hang on a minute, you didn't provide any data to back up that theory'. And you're right! However, often times we don't have all the data available to us, we simply have to use our own experiences and intuition. As an Economics graduate who has also been fascinated with finance from an early age, the theory makes sense to me._\n## Wrapping up\nIn conclusion, data should not be the driver of your decisions. Like an unpredictable friend, data belongs firmly in the passenger seat, preferably with the child-lock on. They can provide suggestions, but ultimately you need to be sceptical before making any decision based off of them.\nRemember, when looking into data, statistics, and/or research, you need to ask yourself:\n  1. Where did this data come from?\n  2. Would this data be presented if the opposite result were true?\n  3. Would I consider the data if the opposite result were true?\n  4. Is there a flaw with the leap from data to insight?\n\n\n## **Final note for data scientists/analysts**\nFor data scientists and analysts, these questions are not just a safeguard - they're a responsibility. As gatekeepers of data-driven insights, your role is crucial in ensuring that decisions are informed by sound reasoning, not just raw numbers and algorithms. By applying this mindset, you can avoid being that unpredictable friend in your organisation. And who know's, one day you may even be invited into the driving seat.\n## Register Now to Continue Reading\n### Unlock Towards Data Science with a Free Account\nAll articles on Towards Data Science are available to registered users. Create a free account today to access this article and thousands more.\nRegister for freeSign in to your account\n* * *\n![](../images/body-be9b2abe4d1a1929d9b6.jpeg)\nWritten By\n## [Cai Parry-Jones](https://towardsdatascience.com/author/caiparryjones96/)\n[See all from Cai Parry-Jones](https://towardsdatascience.com/author/caiparryjones96/)\n[Business Strategy](https://towardsdatascience.com/tag/business-strategy/)[Confirmation Bias](https://towardsdatascience.com/tag/confirmation-bias/)[Data Analysis](https://towardsdatascience.com/tag/data-analysis/)[Data Science](https://towardsdatascience.com/tag/data-science/)[Logic](https://towardsdatascience.com/tag/logic/)\nShare This Article\n  * [](https://www.facebook.com/sharer/sharer.php?u=https%3A%2F%2Ftowardsdatascience.com%2Fstop-being-data-driven-583b5e7abe7b%2F&title=Stop%20Being%20Data-Driven)\n  * [](https://www.linkedin.com/shareArticle?mini=true&url=https%3A%2F%2Ftowardsdatascience.com%2Fstop-being-data-driven-583b5e7abe7b%2F&title=Stop%20Being%20Data-Driven)\n  * [](https://x.com/share?url=https%3A%2F%2Ftowardsdatascience.com%2Fstop-being-data-driven-583b5e7abe7b%2F&text=Stop%20Being%20Data-Driven)\n\n\nTowards Data Science is a community publication. Submit your insights to reach our global audience and earn through the TDS Author Payment Program.\n[Write for TDS](https://towardsdatascience.com/submissions/)\n## Related Articles\n  * [![](../images/002.jpeg)](https://towardsdatascience.com/markov-chain-monte-carlo-in-python-44f7e609be98/)\n## [Markov Chain Monte Carlo in Python](https://towardsdatascience.com/markov-chain-monte-carlo-in-python-44f7e609be98/)\n[](https://towardsdatascience.com/stop-being-data-driven-583b5e7abe7b/)\nA Complete Real-World Implementation The past few months, I encountered one term again and again...\n[Will Koehrsen](https://towardsdatascience.com/author/will%20koehrsen/)\nFebruary 9, 201812 min read\n  * [![](../images/003.jpeg)](https://towardsdatascience.com/analyzing-geospatial-data-with-python-7244c1b9e302/)\n## [Analyzing Geospatial Data with Python](https://towardsdatascience.com/analyzing-geospatial-data-with-python-7244c1b9e302/)\n[Data Science](https://towardsdatascience.com/category/data-science/)\nA practical data analysis post with Python code.\n[Gustavo Santos](https://towardsdatascience.com/author/gustavorsantos/)\nAugust 19, 20237 min read\n  * [![](../images/004.jpg)](https://towardsdatascience.com/confidence-intervals-with-python-bfa28ebb81c/)\n## [Confidence Intervals with Python](https://towardsdatascience.com/confidence-intervals-with-python-bfa28ebb81c/)\n[Machine Learning](https://towardsdatascience.com/category/artificial-intelligence/machine-learning/)\nCollege Statistics with Python\n[Luís Roque](https://towardsdatascience.com/author/luisroque/)\nJune 22, 202114 min read\n  * [![](../images/005.jpg)](https://towardsdatascience.com/temporary-variables-in-python-readability-versus-performance-f6708b5f293c/)\n## [Temporary Variables in Python: Readability versus Performance](https://towardsdatascience.com/temporary-variables-in-python-readability-versus-performance-f6708b5f293c/)\n[Data Science](https://towardsdatascience.com/category/data-science/)\nTemporary variables can make code clearer. What about the performance of such code?\n[Marcin Kozak](https://towardsdatascience.com/author/nyggus/)\nJune 1, 20238 min read\n  * [![](../images/006.jpeg)](https://towardsdatascience.com/attribute-relevance-analysis-in-python-iv-and-woe-b5651443fc04/)\n## [Attribute Relevance Analysis in Python - IV and WoE](https://towardsdatascience.com/attribute-relevance-analysis-in-python-iv-and-woe-b5651443fc04/)\n[Machine Learning](https://towardsdatascience.com/category/artificial-intelligence/machine-learning/)\nRecently I've written about Recursive Feature Elimination - one of many feature selection techniques I use most often. Today I will speak...\n[Dario Radečić](https://towardsdatascience.com/author/radecicdario/)\nSeptember 9, 20199 min read\n  * [![](../images/007.jpg)](https://towardsdatascience.com/the-power-and-pitfalls-of-vector-based-image-search/)\n## [The Power and Pitfalls of Vector-Based Image Search](https://towardsdatascience.com/the-power-and-pitfalls-of-vector-based-image-search/)\n[Artificial Intelligence](https://towardsdatascience.com/category/artificial-intelligence/)\nA hands-on guide to setting up image similarity search in Milvus, and why visual replication isn't always enough.\n[Soner Yıldırım](https://towardsdatascience.com/author/sonery/)\nJune 18, 20267 min read\n  * [![](../images/008.jpg)](https://towardsdatascience.com/the-misconception-of-retraining-why-model-refresh-isnt-always-the-fix/)\n## [The Misconception of Retraining: Why Model Refresh Isn’t Always the Fix](https://towardsdatascience.com/the-misconception-of-retraining-why-model-refresh-isnt-always-the-fix/)\n[Artificial Intelligence](https://towardsdatascience.com/category/artificial-intelligence/)\nRetraining is easy; knowing when not to is the real challenge. In machine learning, performance drops are rarely about stale weights; they’re about misunderstood signals.\n[Shafeeq Ur Rahaman](https://towardsdatascience.com/author/shafeequr.rahaman/)\nJuly 30, 20256 min read\n  * [![](../images/009.jpg)](https://towardsdatascience.com/an-overview-of-the-pep-8-style-guide-5672459c7682/)\n## [An Overview of The PEP 8 Style Guide](https://towardsdatascience.com/an-overview-of-the-pep-8-style-guide-5672459c7682/)\n[Programming](https://towardsdatascience.com/category/programming/)\nHave style with your Python code.\n[Dan Root](https://towardsdatascience.com/author/third_eye_cyborg/)\nOctober 15, 202010 min read\n  * [![](../images/010.jpeg)](https://towardsdatascience.com/exploring-the-tokyo-neighborhoods-data-science-in-real-life-8b6c2454ca16/)\n## [Exploring the Tokyo Neighborhoods: Data-Science in Real Life](https://towardsdatascience.com/exploring-the-tokyo-neighborhoods-data-science-in-real-life-8b6c2454ca16/)\n[Machine Learning](https://towardsdatascience.com/category/artificial-intelligence/machine-learning/)\nWeb-Scrapping, Foursquare API, Folium\n[Saptashwa Bhattacharyya](https://towardsdatascience.com/author/saptashwa/)\nApril 27, 20199 min read\n\n\n  * [YouTube](https://www.youtube.com/c/TowardsDataScience)\n  * [X](https://x.com/TDataScience)\n  * [LinkedIn](https://www.linkedin.com/company/towards-data-science/)\n  * [Threads](https://www.threads.net/@towardsdatascience)\n  * [Bluesky](https://bsky.app/profile/towardsdatascience.com)\n\n\n[](https://towardsdatascience.com/)\nYour home for data science and AI. The world's leading publication for data science, data analytics, data engineering, machine learning, and artificial intelligence professionals.\nSubscribe to Our Newsletter[Write For TDS](https://towardsdatascience.com/submissions/)•[About](https://towardsdatascience.com/about-towards-data-science-d691af11cc2f/)•[Advertise](https://contact.towardsdatascience.com/advertise-with-towards-data-science)•[Privacy Policy](https://towardsdatascience.com/privacy-policy/)•[Terms of Use](https://towardsdatascience.com/website-terms-of-use/)\n© Insight Media Group, LLC 2026•[The New Stack](https://thenewstack.io)•[roadmap.sh](https://roadmap.sh)•[Creator Network](https://insightmediagroup.io/creator-network)\n####  Recommended Articles \nClose\n  * [ ![](https://h030.towardsdatascience.com/rest/v2/contentStores/d7d3a4ab-7caf-4383-bbd2-fbf7fb4f1787/items/607686/image?etag=1782161464448&width=500&height=500) How Relevance Models Foreshadowed Transformers for NLP ](https://towardsdatascience.com/how-relevance-models-foreshadowed-transformers-for-nlp/ \"How Relevance Models Foreshadowed Transformers for NLP\")\n  * [ ![](https://h030.towardsdatascience.com/rest/v2/contentStores/d7d3a4ab-7caf-4383-bbd2-fbf7fb4f1787/items/607639/image?etag=1781250125848&width=500&height=500) Javascript Fatigue: HTMX Is All You Need to Build ChatGPT — Part 1 ](https://towardsdatascience.com/javascript-fatigue-you-dont-need-js-to-build-chatgpt/ \"Javascript Fatigue: HTMX Is All You Need to Build ChatGPT — Part 1\")\n  * [ ![](https://h030.towardsdatascience.com/rest/v2/contentStores/d7d3a4ab-7caf-4383-bbd2-fbf7fb4f1787/items/607930/image?etag=1782124566054&width=500&height=500) The Subset Sum Problem Solved in Linear Time for Dense Enough Inputs ](https://towardsdatascience.com/subset-sum-problem-solved-in-linear-time-for-dense-enough-inputs/ \"The Subset Sum Problem Solved in Linear Time for Dense Enough Inputs\")\n  * [ ![](https://h030.towardsdatascience.com/rest/v2/contentStores/d7d3a4ab-7caf-4383-bbd2-fbf7fb4f1787/items/3660/image?etag=1780176246070&width=500&height=500) Does Your Company Have a Data Strategy? ](https://towardsdatascience.com/does-your-company-have-a-data-strategy-e8944dbec4ae/ \"Does Your Company Have a Data Strategy?\")\n\n\n",
  "metadata": {
    "title": "Stop Being Data-Driven | Towards Data Science",
    "description": "Why we are fooled by data and how to stop it",
    "keywords": null,
    "author": "Cai Parry-Jones",
    "og:locale": "en_US",
    "og:type": "article",
    "og:title": "Stop Being Data-Driven",
    "og:description": "Why we are fooled by data and how to stop it",
    "og:url": "https://towardsdatascience.com/stop-being-data-driven-583b5e7abe7b/",
    "og:site_name": "Towards Data Science",
    "og:image": "https://assets.insightmediagroup.io/media/wp-content/uploads/2024/08/0-DMUzqsJxapVIqS9-scaled.jpg",
    "og:image:width": "2560",
    "og:image:height": "1654",
    "og:image:type": "image/jpeg",
    "twitter:card": "summary_large_image",
    "twitter:site": "@TDataScience",
    "twitter:creator": "@TDataScience",
    "twitter:label1": "Written by",
    "twitter:data1": "Cai Parry-Jones",
    "twitter:label2": "Est. reading time",
    "twitter:data2": "11 min read",
    "article:published_time": "2024-08-29T23:39:17.000Z",
    "article:modified_time": "2024-08-29T23:39:17.000Z",
    "article:author": "https://towardsdatascience.com/author/caiparryjones96/"
  },
  "paywall": {
    "listed_paid": false,
    "detected": false,
    "marker": "",
    "public_only": false,
    "policy": "付费/会员内容只保留页面公开可见部分，不绕过付费墙"
  },
  "crawl": {
    "success": true,
    "status_code": 202,
    "error": ""
  },
  "code_blocks": [],
  "images": [
    {
      "status": "http_404",
      "url": "https://h030.towardsdatascience.com/rest/v2/contentStores/d7d3a4ab-7caf-4383-bbd2-fbf7fb4f1787/items/607686/image?etag=1782161464448&width=500&height=500",
      "src": "https://h030.towardsdatascience.com/rest/v2/contentStores/d7d3a4ab-7caf-4383-bbd2-fbf7fb4f1787/items/607686/image?etag=1782161464448&width=500&height=500",
      "alt": "",
      "downloaded": false,
      "discovery": "saved_markdown",
      "retried_at": "2026-10-20T17:52:05Z"
    },
    {
      "status": "http_404",
      "url": "https://h030.towardsdatascience.com/rest/v2/contentStores/d7d3a4ab-7caf-4383-bbd2-fbf7fb4f1787/items/607639/image?etag=1781250125848&width=500&height=500",
      "src": "https://h030.towardsdatascience.com/rest/v2/contentStores/d7d3a4ab-7caf-4383-bbd2-fbf7fb4f1787/items/607639/image?etag=1781250125848&width=500&height=500",
      "alt": "",
      "downloaded": false,
      "discovery": "saved_markdown",
      "retried_at": "2026-10-20T17:52:05Z"
    },
    {
      "status": "http_404",
      "url": "https://h030.towardsdatascience.com/rest/v2/contentStores/d7d3a4ab-7caf-4383-bbd2-fbf7fb4f1787/items/607930/image?etag=1782124566054&width=500&height=500",
      "src": "https://h030.towardsdatascience.com/rest/v2/contentStores/d7d3a4ab-7caf-4383-bbd2-fbf7fb4f1787/items/607930/image?etag=1782124566054&width=500&height=500",
      "alt": "",
      "downloaded": false,
      "discovery": "saved_markdown",
      "retried_at": "2026-10-20T17:52:05Z"
    },
    {
      "status": "http_404",
      "url": "https://h030.towardsdatascience.com/rest/v2/contentStores/d7d3a4ab-7caf-4383-bbd2-fbf7fb4f1787/items/3660/image?etag=1780176246070&width=500&height=500",
      "src": "https://h030.towardsdatascience.com/rest/v2/contentStores/d7d3a4ab-7caf-4383-bbd2-fbf7fb4f1787/items/3660/image?etag=1780176246070&width=500&height=500",
      "alt": "",
      "downloaded": false,
      "discovery": "saved_markdown",
      "retried_at": "2026-10-20T17:52:05Z"
    }
  ],
  "audio": [],
  "videos": [
    {
      "url": "https://www.youtube.com/watch?v=XAOs-frRfa4",
      "status": "ok",
      "local_path": "attachments/31fae598d8a6/videos/XAOs-frRfa4.mp4",
      "bytes": 247510836,
      "valid": true,
      "height": 1080,
      "width": 1920,
      "duration": "1496.461000"
    },
    {
      "url": "https://www.youtube.com/watch?v=yNK4nXWA_s8",
      "status": "ok",
      "local_path": "attachments/31fae598d8a6/videos/yNK4nXWA_s8.mp4",
      "bytes": 67193105,
      "valid": true,
      "height": 1080,
      "width": 1920,
      "duration": "939.901000"
    },
    {
      "url": "https://www.youtube.com/c/TowardsDataScience",
      "kind": "channel_reference",
      "status": "reference_only"
    }
  ],
  "links": [
    {
      "type": "internal",
      "href": "https://towardsdatascience.com/"
    },
    {
      "type": "internal",
      "href": "https://towardsdatascience.com/latest/"
    },
    {
      "type": "internal",
      "href": "https://towardsdatascience.com/tag/editors-pick/"
    },
    {
      "type": "internal",
      "href": "https://towardsdatascience.com/tag/the-variable/"
    },
    {
      "type": "internal",
      "href": "https://towardsdatascience.com/shipai/"
    },
    {
      "type": "internal",
      "href": "https://towardsdatascience.com/submissions/"
    },
    {
      "type": "internal",
      "href": "https://towardsdatascience.com/category/data-science/"
    },
    {
      "type": "internal",
      "href": "https://towardsdatascience.com/author/caiparryjones96/"
    },
    {
      "type": "internal",
      "href": "https://towardsdatascience.com/tag/business-strategy/"
    },
    {
      "type": "internal",
      "href": "https://towardsdatascience.com/tag/confirmation-bias/"
    },
    {
      "type": "internal",
      "href": "https://towardsdatascience.com/tag/data-analysis/"
    },
    {
      "type": "internal",
      "href": "https://towardsdatascience.com/tag/data-science/"
    },
    {
      "type": "internal",
      "href": "https://towardsdatascience.com/tag/logic/"
    },
    {
      "type": "internal",
      "href": "https://towardsdatascience.com/markov-chain-monte-carlo-in-python-44f7e609be98/"
    },
    {
      "type": "internal",
      "href": "https://towardsdatascience.com/stop-being-data-driven-583b5e7abe7b/"
    },
    {
      "type": "internal",
      "href": "https://towardsdatascience.com/author/will koehrsen/"
    },
    {
      "type": "internal",
      "href": "https://towardsdatascience.com/analyzing-geospatial-data-with-python-7244c1b9e302/"
    },
    {
      "type": "internal",
      "href": "https://towardsdatascience.com/author/gustavorsantos/"
    },
    {
      "type": "internal",
      "href": "https://towardsdatascience.com/confidence-intervals-with-python-bfa28ebb81c/"
    },
    {
      "type": "internal",
      "href": "https://towardsdatascience.com/category/artificial-intelligence/machine-learning/"
    },
    {
      "type": "external",
      "href": "https://write.insightmediagroup.io"
    },
    {
      "type": "external",
      "href": "https://www.linkedin.com/company/towards-data-science/"
    },
    {
      "type": "external",
      "href": "https://x.com/TDataScience"
    },
    {
      "type": "external",
      "href": "https://unsplash.com/"
    },
    {
      "type": "external",
      "href": "https://www.fullstackeconomics.com/p/why-zillow-is-like-my-bad-fantasy-football-team"
    },
    {
      "type": "external",
      "href": "https://www.scientificamerican.com/article/quack-cancer-diets-endanger-people-stick-to-science-backed-medicine/"
    },
    {
      "type": "external",
      "href": "https://www.spectator.co.uk/article/is-diversity-actually-good-for-business/"
    },
    {
      "type": "external",
      "href": "https://roadmap.sh/ai-data-scientist"
    },
    {
      "type": "external",
      "href": "https://www.spectator.co.uk/article/the-unfashionable-truth-about-the-riots/"
    },
    {
      "type": "external",
      "href": "https://www.ons.gov.uk/employmentandlabourmarket/peoplenotinwork/unemployment"
    },
    {
      "type": "external",
      "href": "https://www.nomisweb.co.uk/reports/lmp/la/1946157068/subreports/ea_time_series/report.aspx"
    },
    {
      "type": "external",
      "href": "https://www.nomisweb.co.uk/reports/lmp/la/1946157122/subreports/ea_time_series/report.aspx"
    },
    {
      "type": "external",
      "href": "https://www.nomisweb.co.uk/reports/lmp/la/1946157059/subreports/ea_time_series/report.aspx"
    },
    {
      "type": "external",
      "href": "https://sci-hub.se/10.1073/pnas.1209746109"
    },
    {
      "type": "external",
      "href": "https://www.youtube.com/watch?t=285s&v=XAOs-frRfa4"
    },
    {
      "type": "external",
      "href": "https://www.stjude.org/research/progress/2020/the-benefits-of-being-highly-cited.html"
    },
    {
      "type": "external",
      "href": "https://www.bbc.co.uk/news/science-environment-39054778"
    },
    {
      "type": "external",
      "href": "https://www.pnas.org/doi/10.1073/pnas.1911695117"
    },
    {
      "type": "external",
      "href": "https://datacolada.org/109"
    },
    {
      "type": "external",
      "href": "https://www.youtube.com/watch?v=yNK4nXWA_s8"
    }
  ],
  "repair_version": 2,
  "repaired_at": "2026-10-20T17:27:47Z",
  "source_url": "https://towardsdatascience.com/stop-being-data-driven-583b5e7abe7b/",
  "delivery_status": "unverified",
  "discovery_status": "http_403",
  "missing_reason": "源页面未重新核验:http_403；已按保留正文补采图片",
  "repair_error": "",
  "actual_video_files": [
    {
      "local_path": "attachments/31fae598d8a6/videos/XAOs-frRfa4.mp4",
      "bytes": 247510836,
      "valid": true,
      "height": 1080,
      "width": 1920,
      "duration": "1496.461000",
      "status": "ok"
    },
    {
      "local_path": "attachments/31fae598d8a6/videos/yNK4nXWA_s8.mp4",
      "bytes": 67193105,
      "valid": true,
      "height": 1080,
      "width": 1920,
      "duration": "939.901000",
      "status": "ok"
    }
  ],
  "expected_saved_body_images": 4,
  "image_discovery": "saved_markdown",
  "source_body_markdown": "![Revisit consent button](https://cdn-cookieyes.com/assets/images/revisit.svg)\nWe value your privacy\nWe use cookies to enhance your browsing experience, serve personalised ads or content, and analyse our traffic. By clicking \"Accept All\", you consent to our use of cookies.\nCustomise Reject All Accept All\nCustomise Consent Preferences ![](https://cdn-cookieyes.com/assets/images/close.svg)\nWe use cookies to help you navigate efficiently and perform certain functions. You will find detailed information about all cookies under each consent category below.\nThe cookies that are categorised as \"Necessary\" are stored on your browser as they are essential for enabling the basic functionalities of the site. ... Show more\nNecessaryAlways Active\nNecessary cookies are required to enable the basic features of this site, such as providing secure log-in or adjusting your consent preferences. These cookies do not store any personally identifiable data.\n  * Cookie\nBCTempID\n  * Duration\n10 minutes\n  * Description\nNo description available.\n\n\n  * Cookie\n__cf_bm\n  * Duration\n1 hour\n  * Description\nThis cookie, set by Cloudflare, is used to support Cloudflare Bot Management. \n\n\n  * Cookie\nAWSALBCORS\n  * Duration\n7 days\n  * Description\nAmazon Web Services set this cookie for load balancing.\n\n\n  * Cookie\n_cfuvid\n  * Duration\nsession\n  * Description\nCloudflare sets this cookie to track users across sessions to optimize user experience by maintaining session consistency and providing personalized services\n\n\n  * Cookie\nli_gc\n  * Duration\n6 months\n  * Description\nLinkedin set this cookie for storing visitor's consent regarding using cookies for non-essential purposes.\n\n\n  * Cookie\n__hssrc\n  * Duration\nsession\n  * Description\nThis cookie is set by Hubspot whenever it changes the session cookie. The __hssrc cookie set to 1 indicates that the user has restarted the browser, and if the cookie does not exist, it is assumed to be a new session.\n\n\n  * Cookie\n__hssc\n  * Duration\n1 hour\n  * Description\nHubSpot sets this cookie to keep track of sessions and to determine if HubSpot should increment the session number and timestamps in the __hstc cookie.\n\n\n  * Cookie\nwpEmojiSettingsSupports\n  * Duration\nsession\n  * Description\nWordPress sets this cookie when a user interacts with emojis on a WordPress site. It helps determine if the user's browser can display emojis properly.\n\n\n  * Cookie\nBCSessionID\n  * Duration\n1 year 1 month 4 days\n  * Description\nBlueconic sets this cookie as a unique identifier for the BlueConic profile.\n\n\n  * Cookie\n_octo\n  * Duration\n1 year\n  * Description\nNo description available.\n\n\n  * Cookie\nlogged_in\n  * Duration\n1 year\n  * Description\nNo description available.\n\n\n  * Cookie\n__Secure-YEC\n  * Duration\npast\n  * Description\nYouTube sets this cookie to stores the user's video player preferences using embedded YouTube video\n\n\n  * Cookie\n__eoi\n  * Duration\n6 months\n  * Description\nDescription is currently not available.\n\n\n  * Cookie\nAWSALBTGCORS\n  * Duration\n7 days\n  * Description\nNo description available.\n\n\n  * Cookie\nlogin-status-p\n  * Duration\npast\n  * Description\nDescription is currently not available.\n\n\n  * Cookie\nAWSALBTG\n  * Duration\n7 days\n  * Description\nNo description available.\n\n\n  * Cookie\ncsrf_token\n  * Duration\nsession\n  * Description\nNo description available.\n\n\n  * Cookie\ntoken_v2\n  * Duration\n1 day\n  * Description\nDescription is currently not available.\n\n\n  * Cookie\nD\n  * Duration\n1 year\n  * Description\nDescription is currently not available.\n\n\n  * Cookie\nPHPSESSID\n  * Duration\nsession\n  * Description\nThis cookie is native to PHP applications. The cookie stores and identifies a user's unique session ID to manage user sessions on the website. The cookie is a session cookie and will be deleted when all the browser windows are closed.\n\n\n  * Cookie\nVISITOR_PRIVACY_METADATA\n  * Duration\n6 months\n  * Description\nYouTube sets this cookie to store the user's cookie consent state for the current domain. \n\n\n  * Cookie\ncookietest\n  * Duration\nsession\n  * Description\nThe cookietest cookie is typically used to determine whether the user's browser accepts cookies, essential for website functionality and user experience.\n\n\n  * Cookie\n__Host-airtable-session\n  * Duration\n1 year\n  * Description\nThis cookie is used to enable us to integrate the services of Airtable.\n\n\n  * Cookie\n__Host-airtable-session.sig\n  * Duration\n1 year\n  * Description\nThis cookie is used to enable us to integrate the services of Airtable.\n\n\n  * Cookie\nm\n  * Duration\n1 year 1 month 4 days\n  * Description\nStripe sets this cookie for fraud prevention purposes. It identifies the device used to access the website, allowing the website to be formatted accordingly.\n\n\n  * Cookie\nBIGipServer*\n  * Duration\nsession\n  * Description\nMarketo sets this cookie to collect information about the user's online activity and build a profile about their interests to provide advertisements relevant to the user. \n\n\n  * Cookie\n__cfruid\n  * Duration\nsession\n  * Description\nCloudflare sets this cookie to identify trusted web traffic.\n\n\n  * Cookie\n_GRECAPTCHA\n  * Duration\n6 months\n  * Description\nGoogle Recaptcha service sets this cookie to identify bots to protect the website against malicious spam attacks.\n\n\n  * Cookie\n__Secure-YNID\n  * Duration\n6 months\n  * Description\nGoogle cookie used to protect user security and prevent fraud, especially during the login process.\n\n\n  * Cookie\ncookieyes-consent\n  * Duration\n1 year\n  * Description\nCookieYes sets this cookie to remember users' consent preferences so that their preferences are respected on subsequent visits to this site. It does not collect or store any personal information about the site visitors.\n\n\nFunctional\nFunctional cookies help perform certain functionalities like sharing the content of the website on social media platforms, collecting feedback, and other third-party features.\n  * Cookie\nlidc\n  * Duration\n1 day\n  * Description\nLinkedIn sets the lidc cookie to facilitate data center selection.\n\n\n  * Cookie\nbrw\n  * Duration\n1 year\n  * Description\nNo description available.\n\n\n  * Cookie\nbrwConsent\n  * Duration\n5 minutes\n  * Description\nDescription is currently not available.\n\n\n  * Cookie\nWMF-Uniq\n  * Duration\n1 year\n  * Description\nDescription is currently not available.\n\n\n  * Cookie\nloom_anon_comment\n  * Duration\n1 year\n  * Description\nNo description available.\n\n\n  * Cookie\nloom_referral_video\n  * Duration\nsession\n  * Description\nDescription is currently not available.\n\n\n  * Cookie\nVISITOR_INFO1_LIVE\n  * Duration\n6 months\n  * Description\nA cookie set by YouTube to measure bandwidth that determines whether the user gets the new or old player interface.\n\n\n  * Cookie\nyt-remote-connected-devices\n  * Duration\nNever Expires\n  * Description\nYouTube sets this cookie to store the user's video preferences using embedded YouTube videos.\n\n\n  * Cookie\nytidb::LAST_RESULT_ENTRY_KEY\n  * Duration\nNever Expires\n  * Description\nThe cookie ytidb::LAST_RESULT_ENTRY_KEY is used by YouTube to store the last search result entry that was clicked by the user. This information is used to improve the user experience by providing more relevant search results in the future.\n\n\n  * Cookie\nyt-remote-device-id\n  * Duration\nNever Expires\n  * Description\nYouTube sets this cookie to store the user's video preferences using embedded YouTube videos.\n\n\n  * Cookie\nyt-remote-session-name\n  * Duration\nsession\n  * Description\nThe yt-remote-session-name cookie is used by YouTube to store the user's video player preferences using embedded YouTube video.\n\n\n  * Cookie\nyt-remote-fast-check-period\n  * Duration\nsession\n  * Description\nThe yt-remote-fast-check-period cookie is used by YouTube to store the user's video player preferences for embedded YouTube videos.\n\n\n  * Cookie\nyt-remote-session-app\n  * Duration\nsession\n  * Description\nThe yt-remote-session-app cookie is used by YouTube to store user preferences and information about the interface of the embedded YouTube video player.\n\n\n  * Cookie\nyt-remote-cast-available\n  * Duration\nsession\n  * Description\nThe yt-remote-cast-available cookie is used to store the user's preferences regarding whether casting is available on their YouTube video player.\n\n\n  * Cookie\nyt-remote-cast-installed\n  * Duration\nsession\n  * Description\nThe yt-remote-cast-installed cookie is used to store the user's video player preferences using embedded YouTube video.\n\n\n  * Cookie\ncp_session\n  * Duration\n3 months\n  * Description\nCodepen sets this cookie for Help systems found in the website.\n\n\n  * Cookie\nloid\n  * Duration\n1 year 1 month 4 days\n  * Description\nThis cookie is set by the Reddit. The cookie enables the sharing of content from the website onto the social media platform.\n\n\nAnalytics\nAnalytical cookies are used to understand how visitors interact with the website. These cookies help provide information on metrics such as the number of visitors, bounce rate, traffic source, etc.\n  * Cookie\n__hstc\n  * Duration\n6 months\n  * Description\nHubspot set this main cookie for tracking visitors. It contains the domain, initial timestamp (first visit), last timestamp (last visit), current timestamp (this visit), and session number (increments for each subsequent session).\n\n\n  * Cookie\nhubspotutk\n  * Duration\n6 months\n  * Description\nHubSpot sets this cookie to keep track of the visitors to the website. This cookie is passed to HubSpot on form submission and used when deduplicating contacts.\n\n\n  * Cookie\n_ga\n  * Duration\n1 year 1 month 4 days\n  * Description\nGoogle Analytics sets this cookie to calculate visitor, session and campaign data and track site usage for the site's analytics report. The cookie stores information anonymously and assigns a randomly generated number to recognise unique visitors.\n\n\n  * Cookie\n_ga_*\n  * Duration\n1 year 1 month 4 days\n  * Description\nGoogle Analytics sets this cookie to store and count page views.\n\n\n  * Cookie\n__Host-psifi.analyticsTrace\n  * Duration\n6 hours\n  * Description\nDescription is currently not available.\n\n\n  * Cookie\n__Host-psifi.analyticsTraceV2\n  * Duration\n6 hours\n  * Description\nDescription is currently not available.\n\n\n  * Cookie\n_gh_sess\n  * Duration\nsession\n  * Description\nGitHub sets this cookie for temporary application and framework state between pages like what step the user is on in a multiple step form.\n\n\n  * Cookie\nYSC\n  * Duration\nsession\n  * Description\nYSC cookie is set by Youtube and is used to track the views of embedded videos on Youtube pages.\n\n\n  * Cookie\najs_anonymous_id\n  * Duration\n1 year\n  * Description\nThis cookie is set by Segment to count the number of people who visit a certain site by tracking if they have visited before.\n\n\n  * Cookie\nvuid\n  * Duration\n1 year 1 month 4 days\n  * Description\nVimeo installs this cookie to collect tracking information by setting a unique ID to embed videos on the website. \n\n\nPerformance\nPerformance cookies are used to understand and analyse the key performance indexes of the website which helps in delivering a better user experience for the visitors.\n  * Cookie\nAWSALB\n  * Duration\n7 days\n  * Description\nAWSALB is an application load balancer cookie set by Amazon Web Services to map the session to the target.\n\n\n  * Cookie\nacq\n  * Duration\npast\n  * Description\nDescription is currently not available.\n\n\n  * Cookie\nacq.sig\n  * Duration\npast\n  * Description\nDescription is currently not available.\n\n\n  * Cookie\nptc\n  * Duration\n2 years\n  * Description\nNo description available.\n\n\nAdvertisement\nAdvertisement cookies are used to provide visitors with customised advertisements based on the pages you visited previously and to analyse the effectiveness of the ad campaigns.\n  * Cookie\nmuc_ads\n  * Duration\n1 year 1 month 4 days\n  * Description\nTwitter sets this cookie to collect user behaviour and interaction data to optimize the website.\n\n\n  * Cookie\nguest_id_marketing\n  * Duration\n1 year 1 month 4 days\n  * Description\nTwitter sets this cookie to identify and track the website visitor.\n\n\n  * Cookie\nguest_id_ads\n  * Duration\n1 year 1 month 4 days\n  * Description\nTwitter sets this cookie to identify and track the website visitor.\n\n\n  * Cookie\npersonalization_id\n  * Duration\n1 year 1 month 4 days\n  * Description\nTwitter sets this cookie to integrate and share features for social media and also store information about how the user uses the website, for tracking and targeting.\n\n\n  * Cookie\nguest_id\n  * Duration\n1 year 1 month 4 days\n  * Description\nTwitter sets this cookie to identify and track the website visitor. It registers if a user is signed in to the Twitter platform and collects information about ad preferences.\n\n\n  * Cookie\nbcookie\n  * Duration\n1 year\n  * Description\nLinkedIn sets this cookie from LinkedIn share buttons and ad tags to recognize browser IDs.\n\n\n  * Cookie\n__Secure-ROLLOUT_TOKEN\n  * Duration\n6 months\n  * Description\nYouTube sets this cookie to manage feature rollout and experimentation. It helps Google control which new features or interface changes are shown to users as part of testing and staged rollouts, ensuring consistent experience for a given user during an experiment.\n\n\n  * Cookie\nyt.innertube::nextId\n  * Duration\nNever Expires\n  * Description\nYouTube sets this cookie to register a unique ID to store data on what videos from YouTube the user has seen.\n\n\n  * Cookie\nyt.innertube::requests\n  * Duration\nNever Expires\n  * Description\nYouTube sets this cookie to register a unique ID to store data on what videos from YouTube the user has seen.\n\n\n  * Cookie\nsession_tracker\n  * Duration\nsession\n  * Description\nThis cookie is set by the Reddit. This cookie is used to identify trusted web traffic. It also helps in adverstising on the website.\n\n\n  * Cookie\nedgebucket\n  * Duration\nsession\n  * Description\nReddit sets this cookie to save the information about a log-on Reddit user, for the purpose of advertisement recommendations and updating the content.\n\n\n  * Cookie\ndid\n  * Duration\n1 year\n  * Description\nArbor sets this cookie to show targeted ads to site visitors.This cookie expires after 2 months or 1 year.\n\n\nUncategorised\nOther uncategorised cookies are those that are being analysed and have not been classified into a category as yet.\nNo cookies to display.\nReject All Save My Preferences Accept All\nToggle Search[](https://towardsdatascience.com/)Toggle Mobile Navigation\n[](https://towardsdatascience.com/)\nPublish AI, ML & data-science insights to a global community of data professionals.\nSign in[Submit an Article](https://write.insightmediagroup.io)\n[Latest](https://towardsdatascience.com/latest/)[Editor's Picks](https://towardsdatascience.com/tag/editors-pick/)[Newsletter](https://towardsdatascience.com/tag/the-variable/)[ShipAI](https://towardsdatascience.com/shipai/)\n* * *\n[Write For TDS](https://towardsdatascience.com/submissions/)\n[LinkedIn](https://www.linkedin.com/company/towards-data-science/)[X](https://x.com/TDataScience)Toggle Search\n[Data Science](https://towardsdatascience.com/category/data-science/)\n# Stop Being Data-Driven\nWhy we are fooled by data and how to stop it\n[Cai Parry-Jones](https://towardsdatascience.com/author/caiparryjones96/)\nAugust 29, 202411 min read\n![source: unsplash.com](https://assets.insightmediagroup.io/media/wp-content/uploads/2024/08/0-DMUzqsJxapVIqS9-scaled.jpg)\nsource: [unsplash.com](https://unsplash.com/)\nOften, when making decisions based on data, we feel as if we have made a more intelligent, accurate choice. The reality is a little different. From [real estate purchases](https://www.fullstackeconomics.com/p/why-zillow-is-like-my-bad-fantasy-football-team) to [dietary choices](https://www.scientificamerican.com/article/quack-cancer-diets-endanger-people-stick-to-science-backed-medicine/) to [corporate board selections](https://www.spectator.co.uk/article/is-diversity-actually-good-for-business/), data can be an amazing catalyst to help make the worst decisions.\nImagine data as that brilliant yet unpredictable friend of yours. One moment they're a genius, the next a complete mess. Would you hand them the keys to your beloved Ford Focus? Or would you politely insist they take the passenger seat?\nThis article explores why data belongs firmly in the passenger seat, not behind the wheel. It will examine real-world examples where data-driven decisions could have steered us off course and into the cliff of misinformation. Fortunately, this article also gives actionable, easy-to-use advice on how to avoid such scenarios by following a four-step ladder to assess the quality of data-driven insights:\n  1. Evaluating the data source,\n  2. Considering the bias of the data presenter,\n  3. Recognising the bias of the data reader,\n  4. Identifying any logical missteps between the data and the insight.\n\n\nBy the end of this journey, you'll be better prepared to navigate the road of decision-making, while keeping your unpredictable friend safely buckled in the passenger seat.\nLearn this step by step with the interactive [AI and Data Scientist](https://roadmap.sh/ai-data-scientist) roadmap.\n## TL;DR\n  * Always question the source of the data. If the source isn't credible or isn't provided, don't be shy in rejecting the entire analysis.\n  * Don't hesitate to fact-check claims, especially when they seem counterintuitive.\n  * Be aware of the data presenters bias. Ask yourself if they'd present the same analysis if it led to the opposite conclusion.\n  * Be aware of confirmation bias. Ask yourself if you'd accept the same analysis if it led to the opposite conclusion.\n  * Consider whether the analysis makes logical sense. Just because two things are correlated doesn't mean one causes the other.\n  * Recognise that data interpretation often involves assumptions and leaps in logic. It's crucial to identify and evaluate these leaps using your own judgment.\n\n\n## Question One - Where did the data come from?\nHere is an excerpt from an article published in The Spectator, titled: '[The unfashionable truth about the riots](https://www.spectator.co.uk/article/the-unfashionable-truth-about-the-riots/)'. Its subject is the 2024 anti-immigration riots in the UK.\n> ...I decided to do some checking on the employment stats for some of the northern towns that have seen the worst rioting in the past week. I also checked the 2011 statistics and then compared the two. I should warn you in advance that if you're easily depressed, you should look away now.\n> Back in 2011, the proportion on out-of-work benefits (including incapacity benefit) in Sunderland was 18 per cent; today it is 19 per cent. In 2011 the unemployment figure in Rotherham was 16 per cent; today it is 18 per cent. In Hartlepool, it was 21 per cent; today, 23 per cent.\n>   * [The unfashionable truth about the riots](https://www.spectator.co.uk/article/the-unfashionable-truth-about-the-riots/), The Spectator\n> \n\nSo, where did this data come from?\nIn the example, all we have is \"the employment stats\"... What the heck does that mean? In the UK there isn't a centralised place for employment statistics, so it's far from obvious what data the author is referring to. You might be content with dismissing the data and thus dismissing the rest of the article, since its premise is based on this data. However, I'm a try-hard, so I put on my best Sherlock Holmes hat and set about finding the un-cited data.\nSadly, I am not Sherlock Holmes. Despite considerable online sleuthing, I couldn't find any data that matched the article's. I did, however, find other \"employment stats\". Specifically the Office of National Statistics (ONS)'s [measure of unemployment](https://www.ons.gov.uk/employmentandlabourmarket/peoplenotinwork/unemployment) by region. It paints a very different picture. In fact the polar opposite picture! Of the three areas the article highlights as having reduced in employment since 2011, the ONS in fact finds they all increased!* I'm afraid the only unfashionable truth illuminated by this article is the degradation of news media. (Or was it always like this?)\n_*Data links: [Sunderland](https://www.nomisweb.co.uk/reports/lmp/la/1946157068/subreports/ea_time_series/report.aspx), [Rotherham](https://www.nomisweb.co.uk/reports/lmp/la/1946157122/subreports/ea_time_series/report.aspx), and [Hartlepool](https://www.nomisweb.co.uk/reports/lmp/la/1946157059/subreports/ea_time_series/report.aspx) employment stats._\n## Question Two - What if the opposite result were true?\n> ...Using laboratory and field experiments, we find that signing before–rather than after–the opportunity to cheat makes ethics salient when they are needed most and significantly reduces dishonesty.\n>   * [Signing at the beginning makes ethics salient and decreases dishonest self-reports in comparison to signing at the end](https://sci-hub.se/10.1073/pnas.1209746109), Lisa L. Shu et al.\n> \n\nThis quote comes from the abstract of a highly influential research paper in Behavioural Science. In case you didn't quite understand the quote, since it is written in the classic academic obfuscation style, the quote is saying that signing your name on the top of a document makes you less likely to lie about the document than if you had signed on the bottom.\nThe data came from a collection of researchers based in highly regarded universities, most notably Francesca Gino who was a professor at Harvard Business School at the time of publication. For me, this passes our first question about the data ('Where did the data come from?').\nNext we need to ask: 'Would the data be presented if the opposite result were true?' To answer this we first need to understand a little about the people and/or institutes presenting the data. In this case it is a group of Behavioural Science academics. Academia is a cut-throat industry, with an exceptionally [high failure rate](https://www.youtube.com/watch?v=XAOs-frRfa4&t=285s). Therefore, it is critical for academics to be considered 'successful' as early as possible to avoid being culled. The key factor to determine an academic's success is, unsurprisingly, their work. But how do you measure the quality of their work? A common method is [citation count](https://www.stjude.org/research/progress/2020/the-benefits-of-being-highly-cited.html#:~:text=The%20more%20citations%20you%20have,based%20on%20their%20impact%20factor.), that is the number of times an academic's work is mentioned in the work of other academics.\nThe issue with this is you are far more likely to to be cited if you have an unexpected/interesting result in your paper. Going back to the original quote, do you think a result where there was no difference in honesty between the group who signed at the top vs the bottom of a document would have been nearly as influential? No, because that would have been the expectation. The conclusion is that there is a strong incentive for academics to generate unexpected/interesting results. Therefore, in our example, we should understand that there is a strong bias for the authors to claim a (significant) difference in honesty between the two groups.\nThis sort of bias is so strong that it has led the [majority of scientific research to be unreproducible by fellow academics](https://www.bbc.co.uk/news/science-environment-39054778). Unreproducible means an academic writes a research paper that copies another academic's research paper's method/experiment, but ends up with significantly different results to the original paper. Turning once more to our case study as an example, following the impactful success of the research paper, a number of other studies attempted to run the same or similar experiment. [All results](https://www.pnas.org/doi/10.1073/pnas.1911695117) of the experiments found no correlation between honesty and location of document signature. It turned out the original paper's finding was very likely the result of [data fraud](https://datacolada.org/109). As were a [number of other influential papers](https://www.youtube.com/watch?v=yNK4nXWA_s8) co-authored by the prestigious Harvard professor, Francesca Gino.\nThis sort of skin-in-the-game bias isn't only found in academia. From [tech vendors posting their latest performances vs competitors](https://www.starburst.io/blog/lie-5-vendor-benchmarks-measure-real-world-performance/), to investment banks presenting to prospective clients that they are no. 1 in the league tables*, bias is rife. And it isn't only other people you should be concerned about. The strongest bias of all is most likely you—yes, YOU. Commonly referred to as confirmation bias, it is the tendency to search for, interpret, favour, and recall information in a way that confirms or supports your prior beliefs.\nEver wondered why such a mass of people could be so stupid on so many political topics? Sadly, it is more likely a result of [your own confirmation bias](https://danielnations.medium.com/why-do-republicans-and-democrats-let-other-people-do-their-thinking-dc6d208945e4) than the collective dim-wittedness of millions of people.\nIf you want to avoid the pitfalls of your own biases, as well as the biases of the data presenter, you not only need to ask: 'Would the data be presented if the opposite result were true?' But also: 'Would I consider the data presented if the opposite result were true?' It may be a tough pill to swallow, but overcoming your own bias may enlighten you more than all the research in the world.\n_*_[_May Contain Lies_](https://maycontainlies.com/) _, Alex Edmans. Page 130._\n## Question Three - Is there a flaw with the leap from data to insight?\n> For most university graduates, having a degree pays.\n> Over the course of a lifetime, estimates suggest women can expect to earn about £250,000 more if they have a degree, while the figure is roughly £170,000 for men.\n>   * [The degrees that make you rich... and the ones that don't](https://www.bbc.co.uk/news/education-41693230), BBC News\n> \n\nThis quote comes from the news department of the prestigious British Broadcasting Corporation (BBC). Specifically, their article titled: '[The degrees that make you rich... and the ones that don't](https://www.bbc.co.uk/news/education-41693230)'. First things first, is there a reliable data source?\n![The source. BBC News, The degrees that make you rich... and the ones that don't](https://assets.insightmediagroup.io/media/wp-content/uploads/2024/08/1ejPw85eNRuPOq5sE-3YQzg.png)\nThe source. BBC News, [The degrees that make you rich... and the ones that don't](https://www.bbc.co.uk/news/education-41693230)\nGreat news, the answer is (probably*) yes! The article cites their data from another prestigious organisation, the Institute of Fiscal Studies. You may want to delve deeper into the exact report of the data source, but for a surface-level analysis, I'm happy with where this raw data has come from.\nSecond we want to ask ourselves, 'would this information be presented if the opposite result was true?' Given the BBC has (to my knowledge) no reason to support higher education institutions, it's fair to assume that the BBC would have published an article highlighting no financial benefits to studying at university if the data suggested it.\nHowever, unfortunately, we still can't trust the BBC's findings just yet. We have one final important question to ask: 'Does the analysis make sense?' After looking at the [article](https://www.bbc.co.uk/news/education-41693230)'s chart on average earnings by subject, have a go at answering the following question before moving on to the next paragraph: 'Given people with Medicine degrees earn more than the average degree, does it make sense to assume that the Medicine degree was the cause of the higher salary?'\nMy answer: Medicine degrees are necessary to become qualified doctors, and doctors generally earn a high income. This supports the idea that a Medicine degree is the specific reason for average higher future earnings. On the other hand, you don't just need to pick Medicine, you also need to _be_ picked for Medicine. Given the average A-level results for a UK Medicine graduate is an outstanding [AAA](https://www.medify.co.uk/blog/a-level-requirements#:~:text=Most%20medical%20schools%20require%20AAA,each%20medical%20school%20requires%20below.&text=A*AA%20\\(AAA%20considered%20if,biology%20and%20EPQ%20grade%20B\\)), you could argue the reason for the high average salaries is because the average Medicine student is exceptionally cognitively capable (in academia at least), which has nothing to do with whether they actually chose Medicine as a degree or not.\nWhat about the degree with the second highest average salary, Economics? Unlike Medicine, you don't strictly need an Economics degree to qualify for any specific high-paying jobs. I'd argue an Economics degree is much less likely a direct factor in increasing a graduate's future salary. For example, someone who is genuinely interested in money at school will be more likely to base their career decisions on what pays more. That same person may also be more likely to pick Economics at university.** If that's true, then pushing someone who is not interested in money to study Economics may not benefit their future career or financial prospects as much as the article is implying.\nSimilarly, someone who earns a university degree in general may be little to no better off than if they hadn't gone to university at all. It may simply be a side effect. For example, in the UK [children with wealthy parents are significantly more likely to attend university](https://commonslibrary.parliament.uk/research-briefings/cbp-9195/#:~:text=Pupils%20eligible%20for%20free%20school,second%20year%20in%20higher%20education.). The wealth of their parents may also have an impact on the child's high-paying job prospects; for example, they might provide invaluable knowledge to their children on how to interview, climb the greasy corporate ladder, and/or network. Given this thought process, the article's finding that \"For most university graduates, having a degree pays\" is, at the very least, not a proven fact, and should not be treated as such.\nDeciding what 'makes sense' is subjective; for example, you may not have been convinced by my arguments above. However, it's important to recognise the leaps in assumptions people make from data to insights, and to do your own 'makes sense' assessment before accepting them.\n_*It's important to acknowledge the limitations of time we have on the depth of our investigation. For very serious things you will want to go deeper, but as a pragmatist, it isn't possible for every data analysis we see._\n_**You may be thinking: 'hang on a minute, you didn't provide any data to back up that theory'. And you're right! However, often times we don't have all the data available to us, we simply have to use our own experiences and intuition. As an Economics graduate who has also been fascinated with finance from an early age, the theory makes sense to me._\n## Wrapping up\nIn conclusion, data should not be the driver of your decisions. Like an unpredictable friend, data belongs firmly in the passenger seat, preferably with the child-lock on. They can provide suggestions, but ultimately you need to be sceptical before making any decision based off of them.\nRemember, when looking into data, statistics, and/or research, you need to ask yourself:\n  1. Where did this data come from?\n  2. Would this data be presented if the opposite result were true?\n  3. Would I consider the data if the opposite result were true?\n  4. Is there a flaw with the leap from data to insight?\n\n\n## **Final note for data scientists/analysts**\nFor data scientists and analysts, these questions are not just a safeguard - they're a responsibility. As gatekeepers of data-driven insights, your role is crucial in ensuring that decisions are informed by sound reasoning, not just raw numbers and algorithms. By applying this mindset, you can avoid being that unpredictable friend in your organisation. And who know's, one day you may even be invited into the driving seat.\n## Register Now to Continue Reading\n### Unlock Towards Data Science with a Free Account\nAll articles on Towards Data Science are available to registered users. Create a free account today to access this article and thousands more.\nRegister for freeSign in to your account\n* * *\n![](https://assets.insightmediagroup.io/media/1787657617193_bio6ww.jpeg)\nWritten By\n## [Cai Parry-Jones](https://towardsdatascience.com/author/caiparryjones96/)\n[See all from Cai Parry-Jones](https://towardsdatascience.com/author/caiparryjones96/)\n[Business Strategy](https://towardsdatascience.com/tag/business-strategy/)[Confirmation Bias](https://towardsdatascience.com/tag/confirmation-bias/)[Data Analysis](https://towardsdatascience.com/tag/data-analysis/)[Data Science](https://towardsdatascience.com/tag/data-science/)[Logic](https://towardsdatascience.com/tag/logic/)\nShare This Article\n  * [](https://www.facebook.com/sharer/sharer.php?u=https%3A%2F%2Ftowardsdatascience.com%2Fstop-being-data-driven-583b5e7abe7b%2F&title=Stop%20Being%20Data-Driven)\n  * [](https://www.linkedin.com/shareArticle?mini=true&url=https%3A%2F%2Ftowardsdatascience.com%2Fstop-being-data-driven-583b5e7abe7b%2F&title=Stop%20Being%20Data-Driven)\n  * [](https://x.com/share?url=https%3A%2F%2Ftowardsdatascience.com%2Fstop-being-data-driven-583b5e7abe7b%2F&text=Stop%20Being%20Data-Driven)\n\n\nTowards Data Science is a community publication. Submit your insights to reach our global audience and earn through the TDS Author Payment Program.\n[Write for TDS](https://towardsdatascience.com/submissions/)\n## Related Articles\n  * [![](https://assets.insightmediagroup.io/media/wp-content/uploads/2025/03/image-10.jpeg)](https://towardsdatascience.com/markov-chain-monte-carlo-in-python-44f7e609be98/)\n## [Markov Chain Monte Carlo in Python](https://towardsdatascience.com/markov-chain-monte-carlo-in-python-44f7e609be98/)\n[](https://towardsdatascience.com/stop-being-data-driven-583b5e7abe7b/)\nA Complete Real-World Implementation The past few months, I encountered one term again and again...\n[Will Koehrsen](https://towardsdatascience.com/author/will%20koehrsen/)\nFebruary 9, 201812 min read\n  * [![](https://assets.insightmediagroup.io/media/wp-content/uploads/2023/08/1VZq2cabrC3oYQpSVjXrmzg-scaled.jpeg)](https://towardsdatascience.com/analyzing-geospatial-data-with-python-7244c1b9e302/)\n## [Analyzing Geospatial Data with Python](https://towardsdatascience.com/analyzing-geospatial-data-with-python-7244c1b9e302/)\n[Data Science](https://towardsdatascience.com/category/data-science/)\nA practical data analysis post with Python code.\n[Gustavo Santos](https://towardsdatascience.com/author/gustavorsantos/)\nAugust 19, 20237 min read\n  * [![](https://assets.insightmediagroup.io/media/wp-content/uploads/2021/06/0Y_v2HH1pdICm4f4f.jpg)](https://towardsdatascience.com/confidence-intervals-with-python-bfa28ebb81c/)\n## [Confidence Intervals with Python](https://towardsdatascience.com/confidence-intervals-with-python-bfa28ebb81c/)\n[Machine Learning](https://towardsdatascience.com/category/artificial-intelligence/machine-learning/)\nCollege Statistics with Python\n[Luís Roque](https://towardsdatascience.com/author/luisroque/)\nJune 22, 202114 min read\n  * [![](https://assets.insightmediagroup.io/media/wp-content/uploads/2023/06/0AU8Q9VoE7oU5lvhR-scaled.jpg)](https://towardsdatascience.com/temporary-variables-in-python-readability-versus-performance-f6708b5f293c/)\n## [Temporary Variables in Python: Readability versus Performance](https://towardsdatascience.com/temporary-variables-in-python-readability-versus-performance-f6708b5f293c/)\n[Data Science](https://towardsdatascience.com/category/data-science/)\nTemporary variables can make code clearer. What about the performance of such code?\n[Marcin Kozak](https://towardsdatascience.com/author/nyggus/)\nJune 1, 20238 min read\n  * [![](https://assets.insightmediagroup.io/media/wp-content/uploads/2019/09/1RcO8rGpq36Eqo2LwxZKRNw-scaled.jpeg)](https://towardsdatascience.com/attribute-relevance-analysis-in-python-iv-and-woe-b5651443fc04/)\n## [Attribute Relevance Analysis in Python - IV and WoE](https://towardsdatascience.com/attribute-relevance-analysis-in-python-iv-and-woe-b5651443fc04/)\n[Machine Learning](https://towardsdatascience.com/category/artificial-intelligence/machine-learning/)\nRecently I've written about Recursive Feature Elimination - one of many feature selection techniques I use most often. Today I will speak...\n[Dario Radečić](https://towardsdatascience.com/author/radecicdario/)\nSeptember 9, 20199 min read\n  * [![](https://assets.insightmediagroup.io/media/wp-content/uploads/2026/06/bohdan-stocek-8kCixqfgXjU-unsplash-scaled-1.jpg)](https://towardsdatascience.com/the-power-and-pitfalls-of-vector-based-image-search/)\n## [The Power and Pitfalls of Vector-Based Image Search](https://towardsdatascience.com/the-power-and-pitfalls-of-vector-based-image-search/)\n[Artificial Intelligence](https://towardsdatascience.com/category/artificial-intelligence/)\nA hands-on guide to setting up image similarity search in Milvus, and why visual replication isn't always enough.\n[Soner Yıldırım](https://towardsdatascience.com/author/sonery/)\nJune 18, 20267 min read\n  * [![](https://assets.insightmediagroup.io/media/wp-content/uploads/2025/07/pexels-cookiecutter-1148820-scaled-1.jpg)](https://towardsdatascience.com/the-misconception-of-retraining-why-model-refresh-isnt-always-the-fix/)\n## [The Misconception of Retraining: Why Model Refresh Isn’t Always the Fix](https://towardsdatascience.com/the-misconception-of-retraining-why-model-refresh-isnt-always-the-fix/)\n[Artificial Intelligence](https://towardsdatascience.com/category/artificial-intelligence/)\nRetraining is easy; knowing when not to is the real challenge. In machine learning, performance drops are rarely about stale weights; they’re about misunderstood signals.\n[Shafeeq Ur Rahaman](https://towardsdatascience.com/author/shafeequr.rahaman/)\nJuly 30, 20256 min read\n  * [![](https://assets.insightmediagroup.io/media/wp-content/uploads/2020/10/0MGwhgis8-7h-M0M0-scaled.jpg)](https://towardsdatascience.com/an-overview-of-the-pep-8-style-guide-5672459c7682/)\n## [An Overview of The PEP 8 Style Guide](https://towardsdatascience.com/an-overview-of-the-pep-8-style-guide-5672459c7682/)\n[Programming](https://towardsdatascience.com/category/programming/)\nHave style with your Python code.\n[Dan Root](https://towardsdatascience.com/author/third_eye_cyborg/)\nOctober 15, 202010 min read\n  * [![](https://assets.insightmediagroup.io/media/wp-content/uploads/2019/04/1pQfh4NW-ONktvo297HbC3Q-scaled.jpeg)](https://towardsdatascience.com/exploring-the-tokyo-neighborhoods-data-science-in-real-life-8b6c2454ca16/)\n## [Exploring the Tokyo Neighborhoods: Data-Science in Real Life](https://towardsdatascience.com/exploring-the-tokyo-neighborhoods-data-science-in-real-life-8b6c2454ca16/)\n[Machine Learning](https://towardsdatascience.com/category/artificial-intelligence/machine-learning/)\nWeb-Scrapping, Foursquare API, Folium\n[Saptashwa Bhattacharyya](https://towardsdatascience.com/author/saptashwa/)\nApril 27, 20199 min read\n\n\n  * [YouTube](https://www.youtube.com/c/TowardsDataScience)\n  * [X](https://x.com/TDataScience)\n  * [LinkedIn](https://www.linkedin.com/company/towards-data-science/)\n  * [Threads](https://www.threads.net/@towardsdatascience)\n  * [Bluesky](https://bsky.app/profile/towardsdatascience.com)\n\n\n[](https://towardsdatascience.com/)\nYour home for data science and AI. The world's leading publication for data science, data analytics, data engineering, machine learning, and artificial intelligence professionals.\nSubscribe to Our Newsletter[Write For TDS](https://towardsdatascience.com/submissions/)•[About](https://towardsdatascience.com/about-towards-data-science-d691af11cc2f/)•[Advertise](https://contact.towardsdatascience.com/advertise-with-towards-data-science)•[Privacy Policy](https://towardsdatascience.com/privacy-policy/)•[Terms of Use](https://towardsdatascience.com/website-terms-of-use/)\n© Insight Media Group, LLC 2026•[The New Stack](https://thenewstack.io)•[roadmap.sh](https://roadmap.sh)•[Creator Network](https://insightmediagroup.io/creator-network)\n####  Recommended Articles \nClose\n  * [ ![](https://h030.towardsdatascience.com/rest/v2/contentStores/d7d3a4ab-7caf-4383-bbd2-fbf7fb4f1787/items/607686/image?etag=1782161464448&width=500&height=500) How Relevance Models Foreshadowed Transformers for NLP ](https://towardsdatascience.com/how-relevance-models-foreshadowed-transformers-for-nlp/ \"How Relevance Models Foreshadowed Transformers for NLP\")\n  * [ ![](https://h030.towardsdatascience.com/rest/v2/contentStores/d7d3a4ab-7caf-4383-bbd2-fbf7fb4f1787/items/607639/image?etag=1781250125848&width=500&height=500) Javascript Fatigue: HTMX Is All You Need to Build ChatGPT — Part 1 ](https://towardsdatascience.com/javascript-fatigue-you-dont-need-js-to-build-chatgpt/ \"Javascript Fatigue: HTMX Is All You Need to Build ChatGPT — Part 1\")\n  * [ ![](https://h030.towardsdatascience.com/rest/v2/contentStores/d7d3a4ab-7caf-4383-bbd2-fbf7fb4f1787/items/607930/image?etag=1782124566054&width=500&height=500) The Subset Sum Problem Solved in Linear Time for Dense Enough Inputs ](https://towardsdatascience.com/subset-sum-problem-solved-in-linear-time-for-dense-enough-inputs/ \"The Subset Sum Problem Solved in Linear Time for Dense Enough Inputs\")\n  * [ ![](https://h030.towardsdatascience.com/rest/v2/contentStores/d7d3a4ab-7caf-4383-bbd2-fbf7fb4f1787/items/3660/image?etag=1780176246070&width=500&height=500) Does Your Company Have a Data Strategy? ](https://towardsdatascience.com/does-your-company-have-a-data-strategy-e8944dbec4ae/ \"Does Your Company Have a Data Strategy?\")\n\n\n",
  "body_base_path": "attachments/31fae598d8a6/pages/",
  "body_markdown_path": "attachments/31fae598d8a6/pages/archived-body.md",
  "local_html": "attachments/31fae598d8a6/pages/archived-body.html",
  "body_source": "prior_capture"
}