It would be preposterous to say that they cause each other and that is exactly why it is our example. 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. Some misleading online posts are difficult to spot because they contain both good and bad medical advice. First, although there was an obvious decline, the word rapid is not as justifiableit is certainly less pronounced. What if the measured variables were different? The time an upside down y-axis made "Stand Your Ground" seem much more reasonable. Thats whats going on in your organization.. Likewise, what are the motives behind it? . 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. Prioritize protecting health professionals and journalists from online harassment. Small samples underrepresent your target audience. Assess the impact of health misinformation. What if it was something more believable, like Alzheimers and old age? 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. Grueskin shared some of these insightful examples of misleading statistics in the news in a Twitter thread that became very popular. 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. But while that may be the case, people are duped by data visualizations every day. 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. These controlling measures are essential and should be part of any experiment or survey unfortunately, that isnt always the case. The most recent case happened not too long ago in September 2021. 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? Misinformation spreads especially easily on social media and online retail sites, as well as via search engines. 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. Another unfair method of polling is to ask a question, but precede it with a conditional statement or a statement of fact. Just like we saw with Fox News examples, the manipulation of the axes can completely change the way the information on a graph is perceived. 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. These two questions are likely to provoke far different responses, even though they deal with the same topic of government assistance. Overloading readers with data 9. Ignoring the uncertainty of the collected data or numbers. Omitting the baseline 5. Whether for market intelligence, customer experience, or business reporting, the future of data is now. 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 . Ask a credible source, such as a doctor or nurse, if they have additional information. When creating a graph to portray a statistic, it is natural to assume that the X and Y axes start at zero. Annual Data 3. But this didnt come easy. Fig. See typical methods & real-world examples of misuse of statistics the news, advertising, science & media. No, of course, its a made-up number (even though such a study would be interesting to know but again, could have all the flaws it tries at the same time to point out). Understand the value of data types with this beginner's introduction! Accurate vaccine information is critical and can help stop common myths and rumors. You should only use log scales when there are clear reasons to graph order of magnitude. Under the CCSSM, beginning in the seventh grade, students are expected make comparisons between different samples on the same attribute. There is also no evidence to say that the Florida Law Enforcement Department was purposely deceiving the public. (, Adults Statistical Literacy: Meaning, Components, Responsibilities, National Governors Association Center for Best Practices & Council of Chief State School Officers. The above graph/chart was presented as a point of emphasis. Here's my top five falsehoods-in-figures: 1. 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. You will end up with a statistical error called selective bias. This is reported by the makers of Fosamax accurately as a 56% reduction in risk, which is true but misleading. While certain topics listed here are likely to stir emotion depending on ones point of view, their inclusion is for data demonstration purposes only. Recently, Kellogg's UK was hit with a ban from the ASA (Advertising Standards Authority) after making false health claims in its advert for Special K cereal. xkdc's comic illustrates this very well, to show how the "fastest-growing" claim is a totally relative marketing speech: Likewise, the needed sample size is influenced by the kind of question you ask, the statistical significance you need (clinical study vs business study), and the statistical technique. Therefore, using the first graph, and only the first graph, to disprove global warming is a perfect misleading statistics example. An official website of the United States government. Each kind is calculated differently and gives different information (and a different impression) about the data: The growing number of places people go to for information has made it easier for misinformation to spread at a never-before-seen speed and scale. In a similar fashion, once students have begun to develop an understanding of associationa topic beginning in the eighth grade under CCSSM, and appearing in tertiary statistics as well as quantitative reasoning coursesa time-series plot might be shared, such as the one in Figure 4 taken from this blog post (Acquah Citation2020, May). The graph generated a big controversy on social media, especially on Twitter, where users pointed out that the Georgia Health Department had repeatedly used misleading statistics during the COVID-19 outbreak. Address health misinformation in your community. This video can be used for educational and training purposes. 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. 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. About eight-in-ten U.S. murders in 2021 - 20,958 out of 26,031, or 81% - involved a firearm. 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. With the abundance of health information available today, it can be hard to tell what is true or not. People also read lists articles that other readers of this article have read. Did you know that with a free Taylor & Francis Online account you can gain access to the following benefits? You can be drawn in by the good from what appears to be a reputable source and then can. We then build on these examples to draw connections to how they could be used to enhance statistics teaching and learning, especially as it relates to secondary and introductory tertiary statistics and quantitative reasoning coursework. Oh, wait -- did we say spin? Much like abortion, global warming is another politically charged topic that is likely to arouse emotions. Learn how to identify and avoid sharing health misinformation. Annual Data 3. Although in 2007 the company was forced to pay a $600 million fine for its criminal actions, the consequences of this are still seen to date. Providing solely the percentage of change without the total numbers or sample size will be totally misleading. The selective bias is slightly more discreet for those who do not read the small lines. Proactively address the publics questions. Provide the public with context to avoid skewing their perceptions about ongoing debates on health topics. Reuters / Via reddit.com 2. This rare disease causes the spine of a baby to form improperly and can lead to serious mobility impairments and possible organ malfunctions. The next of our most common examples for misuse of statistics and misleading data is, perhaps, the most serious. Now that we've put the misuse of statistics in context, let's 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. This list of misleading statistics fallacy examples would not be complete without referencing the COVID-19 pandemic. Want to test a professional data analysis software? Spain and Italy have large populations, but enormous. 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. Which saw an increase of millions of visitors in just a couple of years, so far, everything looks normal. Statistics is regularly used by urban planners to decide how many apartments, shops, stores, etc. Consider headlines and images that inform rather than shock or provoke. No matter how good a study might be, if it's not written using objective and formal language, then it is at risk to mislead. Source #1: A small sample size. This is problematic because this plot was used to describe statistical trends directly to the general public. 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 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. Representative Jason Chaffetz of Utah explained: In pink, thats the reduction in the breast exams, and the red is the increase in the abortions. Learn everything there is to know about the power of professional area charts. Type the claim into a search engine to see if it has been verified by a credible source. This is just one of many examples of misleading statistics in the media and politics. These studies are very soon contradicted by other important or outlandish findings. Amplify communications from trusted messengers and subject matter experts. Certain industries tend to have more issues with misleading claims. In 2007, Colgate was ordered by the Advertising Standards Authority (ASA) of the U.K. to abandon their claim: More than 80% of Dentists recommend Colgate. The slogan in question was positioned on an advertising billboard in the U.K. and was deemed to be in breach of U.K. advertising rules. Address health misinformation in your community by working with schools, community groups, and health care professionals to develop local strategies against misinformation. In CCSSM, students gain experiences with histograms beginning in grade 6, and they begin comparing multiple plots as early as the seventh grade. And finally, if youre not sure about the content dont share it. This plot (Figure 2) shows something quite different than the one shared by the Kansas Department of Health and Environment in the August 5 press conference. A study of millions of journal articles shows that their authors are increasingly reporting p-values but are often doing so in a misleading way, according to a study by researchers at the Stanford University School of Medicine.P-values are a measure of statistical significance intended to inform scientific conclusions. 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. After a discussion, and a conclusion that attempts to make a generalized claim beyond the data (i.e., an inference; also a seventh-grade standard), the adjusted plot (Figure 2) could be shared with questions such as: Does the conclusion still hold when the plot is adjusted to accurately depict the two situations? The birth rate for . Now, you might argue that The Times is telling the truth, as they are actually leading over their competitors. The example above is an example of selective bias; the biologists were recruited, not randomly selected. In an undergraduate-level context, it is fairly common to reason about side-by-side histograms, or to create them, in statistics courses or quantitative reasoning courses. Truncating axes means doing the opposite. newrepublic.com / Via reddit.com Advertisement 3. We apologize. A quick look shows that counties with mask mandates (the orange line) in place have shown a stark decline in COVID-19 cases over the course of about 3 weeks that has led to lower case numbers than counties without a mask mandate. Whether this person notices or not, they might be providing an inaccurate or manipulated picture to confirm a specific conclusion. However, when taking a closer look at the graph, we can see that the y-axis is reversed, starting with the highest numbers at the bottom and reaching 0 at the top. Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine. Managing Partners: Martin Blumenau, Ruth Pauline Wachter | Trade Register: Berlin-Charlottenburg HRB 144962 B | Tax Identification Number: DE 28 552 2148, News, Insights and Advice for Getting your Data in Shape, BI Blog | Data Visualization & Analytics Blog | datapine, NASAs Goddard Institute for Space Studies. 1. In critical scenarios such as a global pandemic, this becomes even more important as misinformation can lead to a higher spread and more deaths. During one of Fow News broadcasts, anchor Tucker Carlson displayed a graph saying that the number of Americans identifying as Christians had collapsed over the last decade. Moreover, in both the Pre-K12 and College Report of the Guidelines for Assessment and Instruction in Statistics Education documents (Bargagliotti etal. 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. Looking for U.S. government information and services? There, they speak about two use cases in which COVID-19 information was used in a misleading way. 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.. To learn about our use of cookies and how you can manage your cookie settings, please see our Cookie Policy. please save N95s and surgical masks for our healthcare workers who . The misuse of statistics is a much broader problem that now permeates multiple industries and fields of study. Misuse of statistics often happens in advertisements, politics, news, media, and others. Surveys or studies conducted on a sample size audience often produce results that are so misleading that they are unusable. You are not required to obtain permission to reuse this article in part or whole. Misleading statistics refers to the misuse of numerical data either intentionally or by error. If all this is true, what is the problem with statistics? 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. Just as we have all benefited from efforts to improve air and water quality, limiting the prevalence and impact of misinformation benefits individual and public health. 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. 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? Manipulating the Y-axis+ 6. 3099067 While numbers dont lie, they can in fact be used to mislead with half-truths. Average monthly temperature in New Haven, CT. The pandemic of the novel coronavirus has gripped the entire world and engaged people in consuming scientific informationperhaps more so than any other event in history. The graph shows the growth of COVID-19 cases from March 5 to March 31. Regardless, many people will look at the graph and get a different idea of what the actual difference is, which is an unethical and dangerous practice. examples of misleading statistics in healthcare a comment eurasia group chairman. However, upon closer inspection, you might notice that there are two vertical axes. 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. This is a clear situation in which the axes are manipulated to show a specific result that is misleading. However, the telling of half-truths through study is not only limited to mathematical amateurs. What is a conclusion you could draw from this plot that would not make much sense (i.e., pushing them to make the causation error)? It is a data mining technique where extremely large volumes of data are analyzed for the purpose of discovering relationships between different points. The image below is a great example of this misleading practice. However, more often than not, data dredging is used to assume the existence of relationships without further study. Misleading Data Visualization Examples 1. . Manipulating the Y-axis+ 6. Register a free Taylor & Francis Online account today to boost your research and gain these benefits: Data (Mis)representation and COVID-19: Leveraging Misleading Data Visualizations For Developing Statistical Literacy Across Grades 616, a School of Teacher Preparation, Administration & Leadership, New Mexico State University, Las Cruces, NM, b Department of Curriculum and Instruction, University of Houston, Houston, TX, GAISE College Report ASA Revision Committee. Given the importance of data in todays rapidly evolving digital world, it is important to be familiar with the basics of misleading statistics and oversight. Television is not the only media platform that can provide examples of bad statistics in the news. The plot compared the number of COVID-19 cases over time for counties in Kansas that had mask mandates versus those that did not. 73.6% of statistics are false. Misinformation is information that is false, inaccurate, or misleading according to the best available evidence at the time. After showing this plot to students, some useful questions could be: Fig. 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. See examples and a list of best practices here! If you still want to use the data to make a point, you can make sure to mention the small sample size as a disclaimer. to the .gov website. Many seem wilfully false, created out of, say, a journalist's desire to create a sensation, a government's need to make a political point or an aid agency's wish for more funds. 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. The time 7 million was 5x more than 6 million. Limiting misinformation helps us make more educated decisions for ourselves, our loved ones, and our communities. Health Misinformation Current Priorities of the U.S. Health (2 days ago) Office of the U.S. The problem with correlations is this: if you measure enough variables, eventually it will appear that some of them correlate. On the other side, of 400 patients that arrived in poor condition at Hospital B, 210 survived at a survival rate of 52.5%. Really? Statistics presented without context should be viewed critically. Ebola, for example, kills 50% of the people it infects on average, which is why the doctors who treat it wear hazmat suits. We also discuss the possible source/motivations behind such (mis)representation of the data. This post will help them learn to recognize misleading statistics real other fallacious data It will discuss how this data misleads people. This misleading data example is also referred to as data dredging (and related to flawed correlations). As we mentioned earlier, the sample size is of utmost importance when it comes to deciding the worth of a study or its results. Knowing when data is accurate and complete, and being able to identify discrepancies between numbers and any . If you are the one performing the analysis, for instance generating reports for your job, you can ask yourself a few relevant questions to avoid using misleading statistics. Omitting baselines, or the axis of a graph, is one of the most common ways data is manipulated in graphs. 1. 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. Moreover, this is a common topic appearing in tertiary introductory statistics courses, as well as courses on quantitative reasoning. As no one works for free, it is always interesting to know who sponsors the research. Examples of Misleading Statistics in Healthcare 1. During the pandemic, health misinformation has led people to decline vaccines, reject public health measures, and use unproven treatments. This presents opportunities for statistics educators and statistics teacher educators to reflect on these (mis)representations and leverage them as teaching and learning opportunities to build statistical literacy. . Advanced technology solutions like online reporting software can enhance statistical data models, and provide digital age businesses with a step up on their competition. Many would falsely assume, yes, solely based on the strength of the correlation. Lets put this into perspective with an example of the misuse of statistics in advertising. should be built in a certain area based on population growth patterns. 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. 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). On top of that, the numbers can be hard to interpret, whether that's a . . Drinking tea increases diabetes by 50%, and baldness raises the cardiovascular disease risk up to 70%! Sample size surveys are one example of creating misleading statistics. Using the wrong graph 7. 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. Example 8: Urban Planning. Big data has the ability to provide digital age businesses with a roadmap for efficiency and transparency, and eventually, profitability. U.S. Department of Health and Human Services. Until March 26, the bars' heights correspond to the numbers. Statistics are infamous for their ability and potential to exist as misleading and bad data. secure websites. There are plenty of examples available, but looking to the world of hockey, a team that gets the puck in their opponents' end during a power play and just cycle for two minutes without taking a shot actually waste a two minute opportunity with puck possession.
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