By Dana Litt and Scott Walters, March 24, 2021. The time 7 million was 5x more than 6 million. For example, during the COVID-19 pandemic misinformation has caused people to decline COVID-19 vaccines, reject public health measures such as masking and physical distancing, and use unproven treatments. These examples bring up several concepts that are, under the Common Core State Standards for Mathematics (CCSSM) (NGAC & CCSSO 2010), introduced beginning in the sixth grade, such as understanding differences between histograms and bar charts, as well as drawing comparisons between two samples, leading to an understanding of association (for both continuous data and categorical data) and correlation. Learn how to identify and avoid sharing health misinformation. Prioritize understanding how people are exposed to and affected by misinformation, and how this may vary for different subpopulations. Any sensible person would easily identify the fact that car accidents do not cause bear attacks. Based on the misuse techniques we covered, it is safe to say that this sleight off-hand technique by Colgate is a clear example of misleading statistics in advertising, and would fall under faulty polling and outright bias. To avoid this issue, you should always pick a random sample of people whose background may or may not be related to the topic of the survey. However, upon closer inspection, you might notice that there are two vertical axes. While a malicious intent to blur lines with misleading statistics will surely magnify bias, the intent is not necessary to create misunderstandings. The report, "Births: Preliminary Data for 2009" found that the rate for the youngest teenagers, 10-14 years, fell from 0.6 to 0.5 per 1,000, also the lowest level ever reported. In May 2020, around 5 months after COVID-19 started spreading around the world, the US Georgia Department of Public Health posted a chart that aimed at showing the top 5 counties that had the highest COVID-19 cases in the past 15 days and the number of cases over time. There, they speak about two use cases in which COVID-19 information was used in a misleading way. Truncating axes is a very dangerous false statistics practice, as it can help create wrong narratives around important topics. Cherry Picking 2. You can see a graph that shows the UK National debt from 1995 to 2016. Accepted author version posted online: 12 Apr 2021, Register to receive personalised research and resources by email. Making the difference between the two publications a lot bigger than what it actually is, which is just 10%. The field of statistics is concerned with collecting, analyzing, interpreting, and presenting data.. The cases start growing rapidly, but since March 26, the growth seems to slow down and come closer to the top of the curve. The above graph/chart was presented as a point of emphasis. Now, the obvious answer is going for option A. We took a very obvious one to show you below. Statistics can tell us about trends that are. Listen with empathy, ask questions, provide alternative explanations, and dont expect success from one conversation. Cumulative VS. Omitting the baseline. It is generally agreed upon that the global mean temperature in 1998 was 58.3 degrees Fahrenheit. On Sept. 29, 2015, Republicans from the U.S. Congress questioned Cecile Richards, the president of Planned Parenthood, regarding the misappropriation of $500 million in annual federal funding. Consider headlines and images that inform rather than shock or provoke. A more helpful way to look at this is the NNT (Number needed to treat, defined in statistics using the formula 100/%reduction). Considering the vast differences between, say, mice and elephants, it can be hard to fit 3 ounces and a ton on the same graph. In this case, the goal is not association, but comparison, thereby making it a bit more difficult to initially interpret the data. At a first glance, the graph, which is displayed below, shows a descending trend that starts the year the law was enacted, concluding that Stand Your Grown is responsible for the apparent drop in the number of murders committed using firearms in the years after it was implemented. Take this first example of a misleading graph that proves global warming is real. Television is not the only media platform that can provide examples of bad statistics in the news. It is fixed". We can all benefit from taking steps to improve the quality of health information we consume. As mentioned, this is not the only time Fox News has been criticized because of these situations. 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. With the abundance of health information available today, it can be hard to tell what is true or not. Seasonal flu, meanwhile, only kills around 0.1%. This is problematic because this plot was used to describe statistical trends directly to the general public. A good rule of thumb is to always take polling with a grain of salt and to try to review the questions that were actually presented. Studies foster informed decision-making, sound judgments, and actions carried out on the weight of evidence, not assumptions. organization in the United States. Truncating axes means doing the opposite. The source of the initial criticism appears to have come from The Rachel Maddow Show (yes, the same one that shared a poorly crafted data visualization in Case 1, but carefully dissected the (mis)representation in this case), which can be viewed in a short video tweeted on May 15 by Acyn Torabi. Using the pair of graphs in the first case, a question that could spur thinking about these two phenomenacounties with vs without a mask mandatecould be something like: What does this graph (Figure 1, the one with two axes) make it appear is happening? This video can be used for educational and training purposes. secure websites. Another unfair method of polling is to ask a question, but precede it with a conditional statement or a statement of fact. Instead, we see the dates between April and May interspersed with the aim of making viewers of this graph believe that the cases are gradually decreasing. Basically, there is no problem pro se - but there can be. During the initial stages of COVID, the general public was forced to consume scientific information in the form of data visualizations to stay informed about the current developments of the virus. We apologize. It further appears to indicate that counties with no mask mandate have seen relatively no change in number of daily cases. Overloading readers with data 9. Bias is most likely to take the form of data omissions or adjustments to prove a specific point. The plot compared the number of COVID-19 cases over time for counties in Kansas that had mask mandates versus those that did not. 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. About eight-in-ten U.S. murders in 2021 - 20,958 out of 26,031, or 81% - involved a firearm. 19 Most Misleading Statistics (That Are Technically Correct) By: Cracked Plasticians April 20, 2016 Advertisement When the math adds up, the numbers never lie. For example, picking only a good-performing month to build a sales report will portray a misleading picture of the overall sales performance. As we mentioned earlier, the sample size is of utmost importance when it comes to deciding the worth of a study or its results. As we can see, the X axes here start from 590 instead of zero. Using the wrong graph. The most common ways statistics are misused, besides misinterpretation, are the following: faulty polling, flawed correlations, misleading data visuals, selective bias and small sample size (Lebeid 2018). This graph makes the argument that masks help "flatten the curve" (or lower the rate of growth of COVID-19 cases) by pointing out that countries with mask usage had lower growth rates than countries without mask usage. Evaluate the effectiveness of strategies and policies to prevent and address health misinformation. People also read lists articles that other readers of this article have read. Broad dissemination and consumption of false or misleading health information, amplified by the internet, poses risks to public health and problems for both the health care enterprise and the government. Address health misinformation in your community by working with schools, community groups, and health care professionals to develop local strategies against misinformation. Misinformation is information that is false, inaccurate, or misleading according to the best available evidence at the time. We all need access to trusted sources of information to stay safe and healthy. It also happens to be a topic that is vigorously endorsed by both opponents and proponents via studies. How does the second plot cause you to reconsider the weight of evidence (e.g., Pfannkuch Citation2006; Engledowl and Gorham Blanco Citation2019) supporting your conclusion? The image below is a great example of this misleading practice. Providing solely the percentage of change without the total numbers or sample size will be totally misleading. Yet, as we learned from the Argentinian graph, looks can deceive. However, some have argued that it may have been unintentional (Cairo Citation2020, May 20). Institute of Medicine (US) Committee on Quality of Health Care in America. Fig. Statistics are nfi for to ability and capability to existing as misleading and bad data. On August 6, Steven Strogratz posted the following plot on Twitter (see Figure 2), which was a recreation of the plot produced by the Kansas Department of Health and Environment with the right side vertical scale removed and both categories of data appropriately placed on the same scale. Type the claim into a search engine to see if it has been verified by a credible source. As healthcare is so dominant in the news, I want to show an example of a confusing and misleading graph about a hospital. 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. You can see the updated version below. 19 of the persons respond yes to the survey. For instance, showing a value for 3 months can show radically different trends than showing it over a year. Now that weve looked at examples and common cases of misuse of statistics, you might be wondering, how do I avoid all of this? Registered in England & Wales No. We will discuss this specific case in more detail later in the post. Sears' Bamboo fabric > Parent Company: Sears > Ad changed: yes > Settlement Amount: $475,000 Sears Holdings agreed to pay $475,000 and. On the other side, of 400 patients that arrived in poor condition at Hospital B, 210 survived at a survival rate of 52.5%. If you follow all the steps mentioned above, you should be able to make a clear analysis and correct use of data. Omitting the baseline 5. However, at the time this graph was published, many media publications interpreted the graph as if the deaths dropped, showing how damaging the misuse of graphs and numbers can be. 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. These are examples of loaded questions., A more accurate way of wording the question would be, Do you support government assistance programs for unemployment? or, (even more neutrally) What is your point of view regarding unemployment assistance?, The latter two examples of the original questions eliminate any inference or suggestion from the poller, and thus, are significantly more impartial. Each is likely a result of a third factor, that being: an increased population, due to the high tourism season in the month of June. 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. No, it isn't. The size of India's middle class was 50 . This can lead to poor decision-making due to misinformation. This is a useful way to show how the use of two vertical axes can aid in visualizing association between two phenomena, particularly because the two vertical axes are different unitsallowing for a more accurate comparison. Statistical reliability is crucial in order to ensure the precision and validity of the analysis. Finally, how big was the sample set, and who was part of it? Making this a clear example of how the time period that we chose to portray can significantly change the way people will perceive the information. This is a Simpsons Paradox at its finest, and it happens when the data hides a conditional variable that can significantly influence the results. What Is A Misleading Statistic? Going against convention 8. To avoid situations like this, there is a bunch of healthcare analytics software that assists analysts and average users in the creation of stunning and accurate visualizations for their data. Since the ruling, it has apologised for the 'error'. 73.6% of statistics are false. A trailer video introducing the Community Toolkit that can be used for educational and training purposes. Lets take a look at some of the evidence for and against. Secure .gov websites use HTTPSA lock ( When this paradox goes unnoticed, it can significantly influence the way the data is interpreted, leaving room to believe a certain conclusion or assumption is an absolute truth, when it could change by looking at it from a different perspective. For example, one popular video recommended injecting herbs into the prostate to treat cancer, which is unproven and potentially dangerous. Provide training and resources for grantees working in communities disproportionately affected by misinformation (e.g., areas with lower vaccine confidence). For example, the objective graph literacy scale is a test with 13 items. Absent these elements, visual data representations should be viewed with a grain of salt, taking into account the common data visualization mistakes one can make. Going https://rigorousthemes.com/blog/misleading-data-visualization-examples/ Category: Health Show Health The results provide deceiving information that creates false narratives around a topic. You are not required to obtain permission to reuse this article in part or whole. A first good thing would be, of course, to stand in front of an honest survey/experiment/research pick the one you have beneath your eyes , that has applied the correct techniques of collection and interpretation of data. Ignoring the uncertainty of the collected data or numbers. At the first glance, there may appear to not be anything inherently misleading about this plot (see Figure 1). When Research Evidence is Misleading. The below chart expresses the 30-year change in global mean temperatures. Brian Kemp's said: "The x-axis was set up that way to show descending values to more easily demonstrate peak values and counties on those dates, our mission failed. Use this checklist everytime you come across health-related content you are not sure about. There is also no evidence to say that the Florida Law Enforcement Department was purposely deceiving the public. This example of a misleading use of statistics is perhaps one of the more clear cases of intent to mislead, despite attempts of the administration to make it appear accidentalsee May 19 story about the response in The Atlanta Journal-Constitution (Mariano and Trubey Citation2020). These controlling measures are essential and should be part of any experiment or survey unfortunately, that isnt always the case. So, let's explore some interesting choices of using data visualization tools and discuss why they are misleading. Staying with our example, that would look like this: Given the rising costs to the middle class, do you support government assistance programs?. Engage with your friends and family on the problem of health misinformation. Cherry picking data. The ASA stated that the claim would be understood by readers to mean that 80 percent of dentists recommend Colgate over and above other brands, and the remaining 20 percent would recommend different brands.. The lack of statistical literacy from the public, paired with the fact that organizations didnt always share accurate statistical information, lead to widespread misrepresentation of data. 1. Surgeon General Our Priorities Health Misinformation Health Misinformation With the abundance of health information available today, it can be hard to tell what is true or not. Using a clearly defined scale, here is what the information looks like: Once placed within a clearly defined scale, it becomes evident that while the amount of cancer screenings has in fact decreased, it still far outnumbers the amount of abortion procedures performed yearly. First of all, the X-axis does not have a label, even though according to the chart, it is meant to show the number of cases over time, this doesn't happen. You can be drawn in by the good from what appears to be a reputable source and then can. I have mentioned the most common mistakes that can lead to misleading or misuse of statistics. The issue comes with the second graph that is displayed in the article, in which we see a comparison of full-price sales between The Times and one of its biggest competitors, the Daily Telegraph. For example, starting the axes in a predefined value so that it will affect the way the graph is perceived to achieve a certain conclusion. Yet, closer examination will reveal that the chart has no defined y-axis. Scientists! 5) How To Avoid & Identify The Misuse Of Statistics? Ebola, for example, kills 50% of the people it infects on average, which is why the doctors who treat it wear hazmat suits. To learn about our use of cookies and how you can manage your cookie settings, please see our Cookie Policy. This article provides guidance on best practices for detecting health misinformation and assessing the accuracy of different information sources. Misleading pie chart 4. Source #1: A small sample size. Here are some more examples of missed opportunities to do so. Remember, misuse of statistics can be accidental or purposeful. Each kind is calculated differently and gives different information (and a different impression) about the data: According to a definition by the Stanford Encyclopedia of Philosophy, a Simpsons Paradox is a statistical phenomenon where an association between two variables in a population emerges, disappears or reverses when the population is divided into subpopulations. The time an upside down y-axis made "Stand Your Ground" seem much more reasonable. Businesses and analysts are exposed to making biases when a single person is doing an entire analysis. 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. Use a broader range of credible sourcesparticularly local sources. Misinformation about diseases, illnesses, potential treatments and cures, vaccines, diets, and cosmetic procedures is especially harmful. This example of a misleading use of statistics is perhaps one of the more clear cases of intent to mislead, despite attempts of the administration to make it appear accidentalsee May 19 story about the response in The Atlanta Journal-Constitution (Mariano and Trubey 2020 ). First, although there was an obvious decline, the word rapid is not as justifiableit is certainly less pronounced. Learn how to identify and avoid sharing health misinformation. Yes, spin. When an experiment or a survey is led on a totally not significant sample size, not only will the results be unusable, but the way of presenting them - namely as percentages - will be totally misleading. We all need access to trusted sources of information to stay safe and healthy. Statistical analyses have historically been a stalwart of the high-tech and advanced business industries, and today they are more important than ever. No one buys a magazine where it states that next year, the same thing is going to happen in XYZ market as this year even though it is true. It becomes hard to believe any analysis! Fig. 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. This technique is often used in politics to exaggerate a result that would otherwise be much less interesting. To make sure the reliability is high, there are various techniques to perform the first of them being the control tests, which should have similar results when reproducing an experiment in similar conditions. Understand the value of data types with this beginner's introduction! Examples of Misleading Statistics in Healthcare 1. The problem was, the graph, which is depicted below, was built with a y-axis on a logarithmic scale instead of a linear one, making it look like the rate of change is smaller than it actually is. Depending on the measure, data can be collected from different sources, including medical records, patient surveys, and administrative databases used to pay bills or to manage care. Many would falsely assume, yes, solely based on the strength of the correlation. Figure 1, from the Healthgrades site, shows the results for the first. The selective bias is slightly more discreet for those who do not read the small lines. Global Warming out of Control! There are several mistakes made at the time of the data interpretation. If all this is true, what is the problem with statistics? Survival Rates in Cancer Survival rates are often used as a measure of cancer treatment success. Manipulating the Y-axis+ 6. Researchers should not allow their values, their bias, or their views to impact their research, analysis, or findings, therefore, looking at the way questions and findings are formulated is a good practice. Editors, clients, and people want something new, not something they know; thats why we often end up with an amplification phenomenon that gets echoed and more than it should. Annual Data 3. These false correlations often leave the general public very confused and searching for answers regarding the significance of causation and correlation. 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). Statistical studies can also assist in the marketing of goods or services, and in understanding each target markets unique value drivers. In the sections that follow we will show two cases of widely disseminated data visualizations that (mis)represent the situation they are describing. The next of our most common examples for misuse of statistics and misleading data is, perhaps, the most serious. We found 18 examples of false advertising scandals that have rocked big brands some are still ongoing and not all companies have had to pay up, but each dealt with a fair amount of negative. U.S. Department of Health and Human Services, Reasons to use the Community Toolkit video, Talk to your community about health misinformation, Share Myths and facts about COVID-19 vaccines to Facebook, Share Myths and facts about COVID-19 vaccines to Twitter, Share Myths and facts about COVID-19 vaccines on LinkedIn, Share Myths and facts about COVID-19 vaccines in an email, Share Battling misinformation through health messaging to Facebook, Share Battling misinformation through health messaging to Twitter, Share Battling misinformation through health messaging on LinkedIn, Share Battling misinformation through health messaging in an email, Share Health misinformation video to Facebook, Share Health misinformation video to Twitter, Share Health misinformation video on LinkedIn, Share Health misinformation video in an email, Battling misinformation through health messaging. Christopher Engledowl & Travis Weiland wrote an insightful article called Data (Mis)representation and COVID-19: Leveraging Misleading Data Visualizations For Developing Statistical Literacy Across Grades 616. 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. Consider the following steps to determine if information is accurate: For more information on common types of health misinformation sources, check out our Health Misinformation Community Toolkit. Although researchers have decried the need for statistical literacy among students and society for decades (Wallman Citation1993; Gal Citation2002; Bargagliotti etal. Well, a Simpsons Paradox can happen when an analyst doesnt look at the complete scope of the data. Citation2020; GAISE College Report ASA Revision Committee Citation2016), in particular as it relates to being a critical consumer of statistics. 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. Just one in a long line of brands to falsely claim a product has health benefits, it .
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