. In the sections that follow we will show two cases of widely disseminated data visualizations that (mis)represent the situation they are describing. Furthermore, an essential discussion should center around why specific locations may have had a mask mandate versus why others may not have, and to focus attention on the change over time within each grouprather than comparing between the groups. The size of India's middle class is 300 million people. 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. Studies foster informed decision-making, sound judgments, and actions carried out on the weight of evidence, not assumptions. To Err is Human: Building a Safer Health System 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. While initially, the trend was going towards choosing option A, when grouping surviving patients considering other variables the trend changed to option B. pastor tom mount olive baptist church 0 lego harry potter sets retiring 2022 what is my locality in address. 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. 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. However, some survival rate statistics can be misleading because they don't take into account differences in patient characteristics, such as age, sex, and stage of disease. 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. Sample size is especially important if you analyze results in terms . Source #1: A small sample size. Learn how to identify and avoid sharing health misinformation. Address health misinformation in your community. 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. 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. It would be preposterous to say that they cause each other and that is exactly why it is our example. Sears' Bamboo fabric > Parent Company: Sears > Ad changed: yes > Settlement Amount: $475,000 Sears Holdings agreed to pay $475,000 and. However, misinformation on major public health issues, such as vaccines and diseases, was also high. A more helpful way to look at this is the NNT (Number needed to treat, defined in statistics using the formula 100/%reduction). (labels are clear, axes begin at 0, right chart type, etc) Is the research represented honestly and in an impartial manner? Amongst various videos of success cases of patients, merchandising, and unethical messaging included in Purdues marketing strategy to advertise OxyContin as a safe drug, there was a very interesting graph, used to prove to doctors that the drug was non-addictive because it stayed on the patients blood over time avoiding symptoms of withdrawal. Because "everyone who has an online presence today is a publisher" (Cairo, 2019, p. 103), inaccurate or misleading information and visualizations spread with unprecedented ease, particularly about health (Lawrence, 2020).People tend to perceive data visualizations about COVID-19 as objective representations of their numbers because they associate charts with logical arguments and . Carefully review information in preprints. As healthcare is so dominant in the news, I want to show an example of a confusing and misleading graph about a hospital. Engage with your friends and family on the problem of health misinformation. 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. Expand efforts to build long-term resilience to misinformation, such as educational programs. We apologize. Likewise, what are the motives behind it? Proactively address the publics questions. In this case, the goal is not association, but comparison, thereby making it a bit more difficult to initially interpret the data. please save N95s and surgical masks for our healthcare workers who . Businesses and analysts are exposed to making biases when a single person is doing an entire analysis. Until March 26, the bars' heights correspond to the numbers. Home Uncategorized examples of misleading statistics in healthcare. Do numbers lie? The available information and expert opinion seems to vacillateone year fats are terrible for you and the next they are a health food. Lets look at one of them closely. Going against convention 8. If all this is true, what is the problem with statistics? If youre not sure, dont share. Statistics are infamous for their ability and potential to exist as misleading and bad data. Truncating an axis is another way in which statistics can be misleading. (1 days ago) WebMisleading Data Visualization Examples 1. Bias is most likely to take the form of data omissions or adjustments to prove a specific point. There are different ways in which statistics can be misleading that we will detail later. (Citation2012) titled Case Studies for Quantitative Reasoning: A Casebook of Media Articles. Give researchers access to useful data to properly analyze the spread and impact of misinformation. 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). In the digital age, these capabilities are only further enhanced and harnessed through the implementation of advanced technology and business intelligence software. So, can statistics be manipulated? What is a conclusion you could draw from this plot that would be more accurate (i.e., pushing them to consider association or correlation concepts)? Survival Rates in Cancer Survival rates are often used as a measure of cancer treatment success. Providing solely the percentage of change without the total numbers or sample size will be totally misleading. Quasi-experimental, single-center, before and after studies are enthusiastically performed. These false correlations often leave the general public very confused and searching for answers regarding the significance of causation and correlation. It is easy to see a correlation. 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. The number of people aged 60 years or older will rise from 900 million to 2 billion between 2015 and 2050 (moving from 12% to 22% of the total global population). Educate students and the public on common tactics used by those who spread misinformation online. Population ageing is happening more quickly than in the past. 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. The Cake Is a Lie. Amplify communications from trusted messengers and subject matter experts. Omitting the baseline. Clearly, there is a correlation between the two, but is there causation? Dietary supplement businesses frequently exaggerate the health benefits of their products. By Dana Litt and Scott Walters, March 24, 2021. While numbers dont lie, they can in fact be used to mislead with half-truths. An official website of the Disinformation is when misinformation is used to serve a malicious purpose, such as to trick people into believing something for financial gain or political advantage. While a malicious intent to blur lines with misleading statistics will surely magnify bias, the intent is not necessary to create misunderstandings. Improper bubble sizes 13. The chart points appear to indicate that 327,000 abortions are greater in inherent value than 935,573 cancer screenings. The top 10 most-shared articles that were reviewed by clinicians and scientists for accuracy were: Understand the value of data types with this beginner's introduction! Independent university study group, lab-affiliated research team, consulting company? Omitting data 10. And over the years, tobacco. This is with the same aim of making it seem like the cases are dropping. Invest in quantifying the harms of misinformation and identifying evidence-based interventions. However, a closer look shows that the X-axis starts at 420,000 instead of 0. For instance, the nature of the group of people surveyed: asking a class of college students about the legal drinking age, or a group of retired people about the elderly care system. This misleading tactic is frequently used to make one group look better than another. Now, you might argue that The Times is telling the truth, as they are actually leading over their competitors. Scientists! For these reasons, a firm understanding of data science is an essential skill for professionals. 4 Plot published in Acquah (Citation2020, May) utilizing two vertical axes to compare ice cream consumption and drowning deaths across time to represent association. Big data has the ability to provide digital age businesses with a roadmap for efficiency and transparency, and eventually, profitability. 1. Misuse of statistics often happens in advertisements, politics, news, media, and others. Seeking a relationship between data isnt a misuse per se, however, doing so without a hypothesis is. 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. For example, while France had almost 150 years to adapt to a change . We all need access to trusted sources of information to stay safe and healthy. Together, we have the power to build a healthier information environment. The graph was later republished with organized dates and counties. 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. For example, the objective graph literacy scale is a test with 13 items. It is a reliable indicator of an individual's graph literacy level, but . At the first glance, there may appear to not be anything inherently misleading about this plot (see Figure 1). Establish quality metrics to assess progress in information literacy. An example of misleading statistics is when determining whether to take a medical test for a rare but serious disease like spina bifida. 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 . Considering the vast differences between, say, mice and elephants, it can be hard to fit 3 ounces and a ton on the same graph. What if the measured variables were different? Convene federal, state, local, territorial, tribal, private, nonprofit, and research partners to explore the impact of health misinformation and establish best practices for prevention. 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. Look at the About Us page on the website to see if you can trust the source. This means that there is no definable justification for the placement of the visible measurement lines. When Research Evidence is Misleading. Lets put this into perspective with an example of the misuse of statistics in advertising. 3099067 . Tread carefully, for either knowingly or ignorantly, correlation hunting will continue to exist within statistical studies. It can be difficult to know which sources of information you can trust. This rare disease causes the spine of a baby to form improperly and can lead to serious mobility impairments and possible organ malfunctions. 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. Annual Data 3. We all need access to trusted sources of information to stay safe and healthy. Much like abortion, global warming is another politically charged topic that is likely to arouse emotions. 1 Plot shared by Rachel Maddow on Twitter and live on The Rachel Maddow Show on August 6th, 2020. 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. So, let's explore some interesting choices of using data visualization tools and discuss why they are misleading. Cherry picking data. These are nine of the most misleading product claims. Once hearing this statement, doctors were skeptical, as they knew how dangerously addictive opioids could be to treat chronicle pain. The power of words is huge, therefore, carefully looking at the way a study is written is another great practice to assess its quality. Yet, as we learned from the Argentinian graph, looks can deceive. Verify the accuracy of information by checking with trustworthy and credible sources. We will discuss this specific case in more detail later in the post. Secure .gov websites use HTTPSA lock ( 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. We can all benefit from taking steps to improve the quality of health information we consume. Each kind is calculated differently and gives different information (and a different impression) about the data: To learn about our use of cookies and how you can manage your cookie settings, please see our Cookie Policy. Consider headlines and images that inform rather than shock or provoke. It is worth mentioning that 1998 was one of the hottest years on record due to an abnormally strong El Nio wind current. 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. Ignoring the uncertainty of the collected data or numbers. During the pandemic, health misinformation has led people to decline vaccines, reject public health measures, and use unproven treatments. Although researchers have decried the need for statistical literacy among students and society for decades (Wallman Citation1993; Gal Citation2002; Bargagliotti etal. About eight-in-ten U.S. murders in 2021 - 20,958 out of 26,031, or 81% - involved a firearm. The next of our most common examples for misuse of statistics and misleading data is, perhaps, the most serious. Just like other industries or areas that we will cover on this list of examples, the healthcare industry is not free of the misuse of statistics. Examples of Misleading Statistics in Healthcare 1. Take care to apply data responsibly, ethically, and visually, and watch your transparent corporate identity grow. 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. 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. Truncating axes means doing the opposite. Each year, millions of research hypotheses are tested. 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. Provide training and resources for grantees working in communities disproportionately affected by misinformation (e.g., areas with lower vaccine confidence). 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. 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. (, Comparing Box plot Distributions: A Teachers Reasoning, Enhancing Statistical Literacy: Enriching Our Society, Journal of Statistics and Data Science Education. Misleading statistics are dangerous. Although the hope would be that students recognize the misleading horizontal axis, it is important to point attention directly to it so that students begin to learn to dissect such visualizations by being critical of scalinga common point of intentional or unintentional misrepresentation of dataas they work toward becoming critical consumers. 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. In critical scenarios such as a global pandemic, this becomes even more important as misinformation can lead to a higher spread and more deaths. It usually falls down on the sample of people surveyed. In the image above, we can see a graph showing 77% of Christian Americans in 2009, a number that decreased to 65% in 2019. An official website of the United States government. 19 Most Misleading Statistics (That Are Technically Correct) By: Cracked Plasticians April 20, 2016 Advertisement When the math adds up, the numbers never lie. By taking the following steps, we can protect ourselves and loved ones from harmful misinformation. You should only use log scales when there are clear reasons to graph order of magnitude. Did you know that with a free Taylor & Francis Online account you can gain access to the following benefits? 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. It also happens to be a topic that is vigorously endorsed by both opponents and proponents via studies. For example, picking only a good-performing month to build a sales report will portray a misleading picture of the overall sales performance. 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). As mentioned at the beginning of this article, it has been shown that a third of the scientists admitted that they had questionable research practices, including withholding analytical details and modifying results! Share sensitive information only on official, 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. But this didnt come easy. There are two problems with this. Proactively engage with patients and the public on health misinformation, Use technology and media platforms to share accurate health information with the public. 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. 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. 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 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. As businesses are often forced to follow a difficult-to-interpret market roadmap, statistical methods can help with the planning that is necessary to navigate a landscape filled with potholes, pitfalls, and hostile competition. U.S. Department of Health and Human Services. Let's check those mistakes. For instance, of 100 patients that arrived in poor condition in Hospital A, 30 survived. Under the CCSSM, beginning in the seventh grade, students are expected make comparisons between different samples on the same attribute. Finally, how big was the sample set, and who was part of it? Engage with your friends and family on the problem of health misinformation. For example, are visualizations representing the data accurately? In this case 100/1.2% =88. Cherry Picking 2. If you see this graph, you would obviously think the UKs national debt is higher than ever. 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. This (mis)representation led to exaggerated claims about changes in cases, which was immediately evident when it was reported that Kansas counties that have mask mandates in place have seen a rapid drop in cases, while counties that only recommend their use have seen no decrease in cases, the states top health official said Wednesday (Hegeman Citation2020, August 5, emphasis added). Misinformation is information that is false, inaccurate, or misleading according to the best available evidence at the time. Papaya leaf juice, elderberry, dates, thyme, garlic, jasmine, limes, okra and other herbs, vegetables and exotic fruits were all offered this year as cures for cancer, diabetes, asthma and the flu.. But, what about causation? Misleading Data Visualization Examples 1. 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. 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. 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. organization in the United States. Lets explain this better with an example. 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. Example #1. While numbers dont always have to be fabricated or misleading, it is clear that even societys most trusted numerical gatekeepers are not immune to the carelessness and bias that can arise with statistical interpretation processes. Accurate vaccine information is critical and can help stop common myths and rumors. Sample size surveys are one example of creating misleading statistics. The plot compared the number of COVID-19 cases over time for counties in Kansas that had mask mandates versus those that did not. Example 8: Urban Planning. 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. Seasonal flu, meanwhile, only kills around 0.1%. American network Fox News has been under scrutiny several times throughout the years for showing misleading statistics graphs that seem to purposely portray a conclusion that is not accurate. An infographic with tips on how to talk to your community about health misinformation. If you perform a quantitative analysis, sample sizes under 200 people are usually invalid. 5 Howick Place | London | SW1P 1WG. For example, one popular video recommended injecting herbs into the prostate to treat cancer, which is unproven and potentially dangerous. The most common one is of course correlation versus causation, which always leaves out another (or two or three) factors that are the actual causation of the problem. Proactively address information deficits. Ebola, for example, kills 50% of the people it infects on average, which is why the doctors who treat it wear hazmat suits. Next, in our list of bad statistics examples, we have the case of a popular toothpaste brand. Here are some more examples of missed opportunities to do so. And finally, if youre not sure about the content dont share it. Rather its politicians trying to make a point for their own interest or just someone not understanding the information behind the graphs and charts they create, crime statistics are not free of being misleading. 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. 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. Here are common types of misuse of statistics: Now that you know them, it will be easier to spot them and question all the stats that are given to you every day. Move with urgency toward coordinated, at-scale investment to tackle misinformation. 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. Use a broader range of credible sourcesparticularly local sources. Several Twitter users began attempting to make sense of what the data were actually saying. 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. Looking for U.S. government information and services? That marked the highest percentage since at least 1968, the earliest year for which the CDC has online records. Asking a question to a sample size of 20 people, where 19 answers "yes" (=95% say for yes) versus asking the same question to 1,000 people and 950 answers "yes" (=95% as well): the validity of the percentage is clearly not the same. You will end up with a statistical error called selective bias. If you really want to make a shocking statement, make sure you only include part of the data. Here are a few potential mishaps that commonly lead to misuse: The manner in which questions are phrased can have a huge impact on the way an audience answers them. As an entrepreneur and former consultant, Mark Suster advises in an article, you should wonder who did the primary research of said analysis. 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. Strengthen the monitoring of misinformation. Continue to modernize public health communications. 19 of the persons respond yes to the survey. Registered in England & Wales No. Moreover, this is a common topic appearing in tertiary introductory statistics courses, as well as courses on quantitative reasoning. 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.
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