Now that weve put the misuse of statistics in context, lets look at various digital age examples of statistics that are misleading across five distinct, but related, spectrums: media and politics, news, advertising, science, and healthcare. Why Health Professionals Should Speak Out Against False Beliefs on the However, more often than not, data dredging is used to assume the existence of relationships without further study. However, when considering other factors such as the health conditions in which patients arrived at the hospitals we can drive other conclusions. For example, are visualizations representing the data accurately? Learn everything there is to know about the power of professional area charts. Now, you might be wondering, how can this be misleading? Misleading Statistics - Real World Examples For Misuse of Data Invest in quantifying the harms of misinformation and identifying evidence-based interventions. It demonstrates the change in air temperature (Celsius) from 1998 to 2012. Furthermore, those without the statistical literacy to recognize it, many times, are further convinced that statistics is not a reliable or trustworthy source of evidence. Did we forget to mention the amount of sugar put in the tea or the fact that baldness and old age are related just like cardiovascular disease risks and old age? With the increasing reliance on intelligent solution automation for variable data point comparisons, best practices (i.e., design and scaling) should be implemented prior to comparing data from different sources, datasets, times, and locations. You should only use log scales when there are clear reasons to graph order of magnitude. Misleading Statistics - Real World Examples For Misuse of Data - Bad Misleading Graphs: Real Life Examples - Statistics How To Why so many of the COVID-19 graphs you see are misleading By closing this message, you are consenting to our use of cookies. For example, on a poll seeking tax opinions, lets look at the two potential questions: - Do you believe that you should be taxed so other citizens dont have to work? Statistical reliability is crucial in order to ensure the precision and validity of the analysis. A typical example of amplification often happens with newspapers and journalists, who take one piece of data and need to turn it into headlines thus often out of its original context. Misrepresenting COVID-19: Lying With Charts During the Second Golden A Beginners Introduction To The Most Common Data Types In Programming, A Complete Guide To Spider Charts With Best Practices And Examples Of When To Use Them, A Beginners Guide To The Power Of Area Charts See Examples, Types & Best Practices, Using percentage change in combination with a small sample size. For instance, showing a value for 3 months can show radically different trends than showing it over a year. 19 of the persons respond yes to the survey. More recently, other studies led by Dr. Loeb found similarly misleading information about prostate cancer on TikTok and Instagram. 4 Plot published in Acquah (Citation2020, May) utilizing two vertical axes to compare ice cream consumption and drowning deaths across time to represent association. Lets take a look at some of the evidence for and against. For this last question, it would be important to make sure students are not merely concluding mask mandates lead to higher case rates than not having them. By taking the following steps, we can protect ourselves and loved ones from harmful misinformation. Prioritize protecting health professionals and journalists from online harassment. And finally, if youre not sure about the content dont share it. Why most published research findings are false. That means there will likely be six possible explanations: - Car accidents (A) cause bear attacks (B), - Bear attacks (B) cause car accidents (A), - Car accidents (A) and bear attacks (B) partly cause each other, - Car accidents (A) and bear attacks (B) are caused by a third factor (C), - Bear attacks (B) are caused by a third factor (C) which correlates to car accidents (A). Engage with your friends and family on the problem of health misinformation. When Research Evidence is Misleading - Journal of Ethics From there naturally stems the question: who paid them? Now, as we learned throughout this post, we cant say with certainty that the law caused the rise in deaths as there are other factors that could influence that number. Increase investment in research on misinformation. The scientists estimated that, of the articles on the top 10 list, the ones with very low credibility scores received 2.1 million shares, while the neutral articles received 2.6 million shares, and the most credible ones received 1.7 million shares. Here is a guide from the CDC on the myths and facts about COVID-19 vaccination. This rare disease causes the spine of a baby to form improperly and can lead to serious mobility impairments and possible organ malfunctions. The prevalence of health misinformation was the highest on Twitter and on issues related to smoking products and drugs. It is generally agreed upon that the global mean temperature in 1998 was 58.3 degrees Fahrenheit. 5 Ways Writers Use Misleading Graphs To Manipulate You - Venngage Sample size surveys are one example of creating misleading statistics. The second problem with having two vertical axes is that the two axes are on different scales, despite the fact that, in this case, they are representing the same measurement (daily number of cases). An official website of the 18 False Advertising Scandals - Business Insider Second, without paying very close attention to the scales of the two vertical axes in the original plot, it would be easy to conclude that counties with mask mandates had dropped below that of those with no mask mandatean incorrect conclusion. Yet, as we learned from the Argentinian graph, looks can deceive. Many would falsely assume, yes, solely based on the strength of the correlation. Going https://rigorousthemes.com/blog/misleading-data-visualization-examples/ Category: Health Show Health In the field of healthcare, statistics is important for the following reasons: Reason 1: Statistics allows healthcare professionals to monitor the health of individuals using descriptive statistics.. Reason 2: Statistics allows healthcare professionals to quantify the relationship between . Data dredging is a self-serving technique often employed for the unethical purpose of circumventing traditional data mining techniques, in order to seek additional conclusions that do not exist. When the Georgia Department of Public Health posted this plot (see Figure 3), it went viral because of what may have been intentional data manipulation. This is known as the misuse of statistics. It is often assumed that the misuse of statistics is limited to those individuals or companies seeking to gain profit from distorting the truth, be it economics, education, or mass media. 15 Misleading Data Visualization Examples - Rigorous Themes Studies foster informed decision-making, sound judgments, and actions carried out on the weight of evidence, not assumptions. Here Are the Most Misleading Product Claims | Time A 22-page overview of health misinformation and resources to stop it. This trailer video introduces the Surgeon Generals Confronting Health Misinformation advisory and why it matters. Statistics - Using the Truth to Mislead - The Health Care Blog Duo writes about how health statistics can mislead The ASA continued, Because we understood that another competitors brand was recommended almost as much as the Colgate brand by the dentists surveyed, we concluded that the claim misleadingly implied 80 percent of dentists recommend Colgate toothpaste in preference to all other brands. The ASA also claimed that the scripts used for the survey informed the participants that the study was being performed by an independent research company, which was inherently false. PLoS Med. Thus, there are no. At a glance, the chart makes you believe that The Times has twice as many full-price subscriptions as its competitor. This misleading tactic is frequently used to make one group look better than another. Definition of Misleading Statistics Statistics is the practice of collecting, organizing, and representing large amounts of numerical data. Statistics Can Be Misleading, Especially During a Pandemic Give researchers access to useful data to properly analyze the spread and impact of misinformation. They can lead to misleading statistics that give you a faulty idea of customer satisfaction and product preferences. We will discuss this specific case in more detail later in the post. Stopping COVID-19 with Misleading Graphs | by Nikita Kotsehub | Towards In the digital age, these capabilities are only further enhanced and harnessed through the implementation of advanced technology and business intelligence software. Any sensible person would easily identify the fact that car accidents do not cause bear attacks. Misleading Healthcare Graph Sometimes, it is better to just make a simple bar or even a table with a couple of columns so that something like this won't happen. Likewise, what are the motives behind it? As an exercise in due diligence, we will review some of the most common forms of misuse of statistics, and various alarming (and sadly, common) misleading statistics examples from public life. Purposely or not, the time periods we choose to portray will affect the way viewers perceive the data. Mixing up linear and logarithmic scales. This is not to say that there is no proper use of data mining, as it can in fact lead to surprise outliers and interesting analyses. Ignoring the uncertainty of the collected data or numbers. Fig. Such examples that appear in the purview of the general public have potential for motivating critical discourse around statistics content and interpretation that can lead to further curiosity of more advanced statistical thinking and reasoning. Really? Using the wrong graph. After showing this plot to students, some useful questions could be: Fig. Controlling the spread of misinformation Take care to apply data responsibly, ethically, and visually, and watch your transparent corporate identity grow. As an entrepreneur and former consultant, Mark Suster advises in an article, you should wonder who did the primary research of said analysis. For example, if an urban planner sees that population growth in a certain part of the city is increasing at an exponential rate compared to other . Truncating axes is a very dangerous false statistics practice, as it can help create wrong narratives around important topics. Address health misinformation in your community. Taking that into account, what the graph is actually showing is an increase in deaths using firearms after the law was enacted. Likewise, another common practice with data is omission, meaning that after looking at a large data set of answers, you only pick the ones that are supporting your views and findings and leave out those that contradict them. Finally, how big was the sample set, and who was part of it? In this case 100/1.2% =88. This is according to NASAs Goddard Institute for Space Studies. Misleading p-values showing up more often in biomedical journal Here's my top five falsehoods-in-figures: 1. A slideshow version of the Community Toolkit for educators and other community leaders. It becomes hard to believe any analysis! For some effective examples of visual information, check out this visualization of wealth shown to scale, or Nicky Case's website, which is full of interactive games that explain how society works. Quasi-experimental, single-center, before and after studies are enthusiastically performed. Examples of misuse of statistics in the media are very common. 1 Plot shared by Rachel Maddow on Twitter and live on The Rachel Maddow Show on August 6th, 2020. When creating a graph to portray a statistic, it is natural to assume that the X and Y axes start at zero. Misleading Statistics: Examples of Techniques Used . Misleading Statistics Can Be Dangerous (Some Examples) Strengthen and scale the use of evidence-based educational programs that build resilience to misinformation. Each of these sources may have other primary purposes, so there are advantages and challenges when they are used for the purposes of quality measurement and reporting. Well, a Simpsons Paradox can happen when an analyst doesnt look at the complete scope of the data. Based on the structure of the chart, it does in fact appear to show that the number of abortions since 2006 experienced substantial growth, while the number of cancer screenings substantially decreased. People also read lists articles that other readers of this article have read. With the abundance of health information available today, it can be hard to tell what is true or not. 1. Misleading Data Visualization Real Life Examples - XB Software Scientists! Cited by lists all citing articles based on Crossref citations.Articles with the Crossref icon will open in a new tab. Root Cause Analysis and Medical Error Prevention We took a very obvious one to show you below. For these reasons, a firm understanding of data science is an essential skill for professionals. Imagine you are in need of risky emergency surgery and have to choose between going to hospitals A or B to get it. Moreover, this is a common topic appearing in tertiary introductory statistics courses, as well as courses on quantitative reasoning. (1 days ago) WebMisleading Data Visualization Examples 1. Datasets are analyzed in ad hoc and exploratory ways. Specific wording patterns have a persuasive effect and induce respondents to answer in a predictable manner. Tufte (Citation2001) talked about this in his book, The Visual Display of Quantitative Information, making a point that having two vertical axes on a time series plot can be very useful when attempting to show a plausible association between two things. Whether this person notices or not, they might be providing an inaccurate or manipulated picture to confirm a specific conclusion. This is problematic because this plot was used to describe statistical trends directly to the general public. There is also the broader context here, which is counties with mask mandates are oftentimes counties that are more densely populated and are seeing larger numbers of cases prompting them to take action. Another common misuse of statistics is strategically picking the time period to show a result. It is, therefore, argued by global warming opponents that, as there was a 0.1-degree decrease in the global mean temperature over a 14-year period, global warming is disproved. Annual Data 3. The most recent case happened not too long ago in September 2021. In critical scenarios such as a global pandemic, this becomes even more important as misinformation can lead to a higher spread and more deaths. As a result, the lack of statistical literacy among the general public, as well as organizations that have a responsibility to share accurate, clear, and timely information with the general public, has resulted in widespread (mis)representations and (mis)interpretations. On August 6, 2020, Rachel Maddow of MSNBC tweeted Chart: Kansas mask counties versus no-mask mandate counties (Maddow Citation2020, August 6) along with a link to a plot (see Figure 1) created by the Kansas Department of Health and Environmentwhich was also shared live on The Rachel Maddow Show that same day. The case started when the giant pharmaceutical company, Purdue Pharma, launched its new product OxyContin, which they advertised as a safe, non-addictive opioid that was highly effective for pain relief. Some misleading online posts are difficult to spot because they contain both good and bad medical advice. Engage with your friends and family on the problem of health misinformation. This is a Simpsons Paradox at its finest, and it happens when the data hides a conditional variable that can significantly influence the results. Representative Jason Chaffetz of Utah explained: In pink, thats the reduction in the breast exams, and the red is the increase in the abortions. Do numbers lie? Misleading statistics refers to the misuse of numerical data either intentionally or by error. The below graph is the one most often referenced to disprove global warming. newrepublic.com / Via reddit.com Advertisement 3. One of the most misleading, but rather common, tricks is to use relative risks when talking about the benefits of a treatment, for example to say that "Women taking tamoxifen had about 49% fewer diagnoses of breast cancer", while potential harms are given in absolute risks: "The annual rate of uterine cancer in the tamoxifen arm was 30 per 10,000 - Do you think that the government should help those people who cannot find work? Now, the obvious answer is going for option A. Here are some more examples of missed opportunities to do so. Was there a rapid decline in cases? To illustrate, a survey asks 20 people a yes-or-no question. This is just one of many examples of misleading statistics in the media and politics. The article, titled The Times leaves the rest behind started by displaying a graphic of the exponential growth of The Times website visitors from 2004 to 2006. We can all benefit from taking steps to improve the quality of health information we consume. People who were more susceptible to . For example, if you have a data set with a diastolic blood pressure range of 230 (highest diastolic value) to 25 (lowest diastolic value) = 205 (range), an error probably exists in your data because the values of 230 and 25 aren't valid blood pressure measures in most studies. Official websites use .govA .gov website belongs to an official government The graph was later republished with organized dates and counties. The Importance of Statistics in Healthcare (With Examples) Now that weve looked at examples and common cases of misuse of statistics, you might be wondering, how do I avoid all of this? Research 101: Descriptive statistics - American Nurse Today It further appears to indicate that counties with no mask mandate have seen relatively no change in number of daily cases. Spain and Italy have large populations, but enormous. For example, the objective graph literacy scale is a test with 13 items. Basically, there is no problem pro se - but there can be. While certain topics listed here are likely to stir emotion depending on ones point of view, their inclusion is for data demonstration purposes only. Misleading Statistics Examples In Healthcare However, closer inspection reveals that the dates along the horizontal axis are not in order of time, with, for instance, May 1 appearing before April 30 and April 26 appearing in between May 7 (on the left) and May 3 (on the right). There, they speak about two use cases in which COVID-19 information was used in a misleading way. Why did the first plot look so different? Each year, millions of research hypotheses are tested. This video can be used for educational and training purposes. We also discuss the possible source/motivations behind such (mis)representation of the data. 1. Misleading Coronavirus graphs. Example #1. In this case, there is no way to know if the data were purposefully (mis)represented to support a particular message, or if it were (mis)represented by accident. Lets look at one of them closely. When Research Evidence is Misleading. A more helpful way to look at this is the NNT (Number needed to treat, defined in statistics using the formula 100/%reduction). Luxembourg and Andorra are in the top 10 largely because of their exceptionally small populations (roughly 600,000 and 77,000, respectively). The cases start growing rapidly, but since March 26, the growth seems to slow down and come closer to the top of the curve. A controversial representation of this happened in 2014 when a graph depicting the number of murders committed using firearms in Florida from 1990 to 2010 was published in the context of the Stand Your Ground law, enacted in 2005 to give people the right to use deadly force for self-defense. Incentivize coordination across grantees to maximize reach, avoid duplication, and bring together a diversity of expertise. How inclusive was it? Collecting data from too small a group can skew your survey and test results. (, Comparing Box plot Distributions: A Teachers Reasoning, Enhancing Statistical Literacy: Enriching Our Society, Journal of Statistics and Data Science Education. While initially, the trend was going towards choosing option A, when grouping surviving patients considering other variables the trend changed to option B. Expand efforts to build long-term resilience to misinformation, such as educational programs. please save N95s and surgical masks for our healthcare workers who . Thats whats going on in your organization.. Want to test a professional data analysis software? Citation2020; GAISE College Report ASA Revision Committee Citation2016), in particular as it relates to being a critical consumer of statistics. The 10 most-shared health news stories of 2018. (Warning - Advisory The chart points appear to indicate that 327,000 abortions are greater in inherent value than 935,573 cancer screenings. Content. As such, this is a great misleading statistics example, and some could argue bias considering that the chart originated not from the Congressman, but from Americans United for Life, an anti-abortion group. There are two take-aways when comparing the two plots. Global Warming out of Control! Likewise, in order to ensure you keep a certain distance to the studies and surveys you read, remember the questions to ask yourself - who researched and why, who paid for it, and what was the sample. The novel coronavirus has forced the world to interact with data visualizations in order to make decisions at the individual level that have, sometimes, grave consequences. Uncover the power of spider charts with this complete guide including examples, best practices, and more! In 2006, The Times, a popular UK newspaper, printed a story about how they were the leading paper both online and in print in the UK. 10 facts on ageing and health - WHO examples of misleading statistics in healthcare a comment eurasia group chairman. Six brands that have made false health claims in advertising - Econsultancy What would your conclusion be about the importance of a mask mandate? The claim, which was based on surveys of dentists and hygienists carried out by the manufacturer, was found to be misrepresentative as it allowed the participants to select one or more toothpaste brands. Knowing when data is accurate and complete, and being able to identify discrepancies between numbers and any . Misinformation spreads especially easily on social media and online retail sites, as well as via search engines. Misleading pie chart 4. Clearly, there is a correlation between the two, but is there causation? You are not required to obtain permission to reuse this article in part or whole. Proactively engage with patients and the public on health misinformation, Use technology and media platforms to share accurate health information with the public. The plot that was originally posted to the Georgia Department of Public Health website (image provided by Twitter user Calling Bullshit, Figure 3) appears to show that the number of COVID-19 cases in the top five counties in the state, at the time, were consistently dropping over the previous month. 5 Howick Place | London | SW1P 1WG. Statistics are infamous for their ability and potential to exist as misleading and bad data. In this article, we showcase examples of how data related to the COVID-19 pandemic has been (mis)represented in the media and by governmental agencies and discuss plausible reasons why it has been (mis)represented. The Worst Covid-19 Misleading Graphs - DataScienceCentral.com How to spot misleading science reporting - QB3 Berkeley Insightful graphs and charts include a very basic, but essential, grouping of elements. Learn how to identify and avoid sharing health misinformation. As we mentioned earlier, the sample size is of utmost importance when it comes to deciding the worth of a study or its results. Here are five techniques for fudging the numbers with misleading statistics examples: Technique #1: Citing Misleading "Averages" The first technique is using the word "average" without specifying what kind of average a figure represents. should be built in a certain area based on population growth patterns. Prioritize early detection of misinformation super-spreaders and repeat offenders. (Citation2012) titled Case Studies for Quantitative Reasoning: A Casebook of Media Articles. These two questions are likely to provoke far different responses, even though they deal with the same topic of government assistance.