Secure .gov websites use HTTPSA lock ( Moreover, in both the Pre-K12 and College Report of the Guidelines for Assessment and Instruction in Statistics Education documents (Bargagliotti etal. To illustrate, a survey asks 20 people a yes-or-no question. Statistical analyses have historically been a stalwart of the high-tech and advanced business industries, and today they are more important than ever. Let's check those mistakes. Example 8: Urban Planning. Partner with community groups and other local organizations to prevent and address health misinformation. Ebola, for example, kills 50% of the people it infects on average, which is why the doctors who treat it wear hazmat suits. 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. Misuse of statistics often happens in advertisements, politics, news, media, and others. This page includes the key takeaways from the advisory. A slideshow version of the Community Toolkit for educators and other community leaders. Moreover, this is a common topic appearing in tertiary introductory statistics courses, as well as courses on quantitative reasoning. As individuals, we can help stop the spread of misinformation by taking the following steps: Everyone has the power to stop misinformation from spreading. Increase investment in research on misinformation. 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). To Err is Human: Building a Safer Health System Making the difference between the two publications a lot bigger than what it actually is, which is just 10%. Another way of creating misleading statistics, also linked with the choice of sample discussed above, is the size of said sample. Annual Data 3. Do numbers lie? There are several mistakes made at the time of the data interpretation. 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. 2 Steven Strogatzs Twitter comment to show a recreation of a plot showing the number of daily cases of COVID-19 per 100,000 in the population of Kansas. The most recent case happened not too long ago in September 2021. 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. Thats whats going on in your organization.. 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. From there naturally stems the question: who paid them? Example #1. Going against conventions. As healthcare is so dominant in the news, I want to show an example of a confusing and misleading graph about a hospital. An infographic with tips on how to talk to your community about health misinformation. We note that these examples come from the context of the United States as that is the context the authors are most familiar with, however, from scanning the news, these seem to be issues common across the world during this highly politicized global pandemic where peoples lives and politicians power are in danger. What if it was something more believable, like Alzheimers and old age? Fact 1: The world's population is rapidly ageing. . Statistical reliability is crucial in order to ensure the precision and validity of the analysis. 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. These controlling measures are essential and should be part of any experiment or survey unfortunately, that isnt always the case. Oh, wait -- did we say spin? Why did the first plot look so different? 4 Plot published in Acquah (Citation2020, May) utilizing two vertical axes to compare ice cream consumption and drowning deaths across time to represent association. Look at the About Us page on the website to see if you can trust the source. Misleading pie chart 4. You will end up with a statistical error called selective bias. . 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. Yet, as we learned from the Argentinian graph, looks can deceive. ) or https:// means youve safely connected 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. The example above is an example of selective bias; the biologists were recruited, not randomly selected. Many would falsely assume, yes, solely based on the strength of the correlation. Manipulating the Y-axis+ 6. Is the language being used objective and formal? This post will help them learn to recognize misleading statistics real other fallacious data It will discuss how this data misleads people. - Do you think that the government should help those people who cannot find work? The prevalence of health misinformation was the highest on Twitter and on issues related to smoking products and drugs. By Nikki Gilliland July 25th 2016. Surveys or studies conducted on a sample size audience often produce results that are so misleading that they are unusable. An official website of the United States government. Here is a guide from the CDC on the myths and facts about COVID-19 vaccination. Sample size is especially important if you analyze results in terms . What information is missing from this data? Reuters / Via reddit.com 2. Misinformation about diseases, illnesses, potential treatments and cures, vaccines, diets, and cosmetic procedures is especially harmful. Be prepared to be confused. Ioannidis JP. 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. Moreover, we believe these kinds of examples are useful in expanding the toolkit of resources available that are in line with other similar resources, such as the book published by Madison etal. 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. Amplify communications from trusted messengers and subject matter experts. While numbers dont lie, they can in fact be used to mislead with half-truths. 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. pastor tom mount olive baptist church 0 lego harry potter sets retiring 2022 what is my locality in address. 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). Misuse of statistics is present everywhere and news outlets are no exception. Basically, there is no problem pro se - but there can be. 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. Luxembourg and Andorra are in the top 10 largely because of their exceptionally small populations (roughly 600,000 and 77,000, respectively). 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. The Surgeon Generals Community Toolkit for Addressing Health Misinformation provides specific guidance and resources for health care providers, educators, librarians, faith leaders, and trusted community members to understand, identify, and stop the spread of health misinformation in their communities. As one out of twenty will inevitably be deemed significant without any direct correlation, studies can be manipulated (with enough data) to prove a correlation that does not exist or that is not significant enough to prove causation. Increase resources and technical assistance to state and local public health agencies to help them better address questions, concerns, and misinformation. 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. They sure can. This is just one of many examples of misleading statistics in the media and politics. This is problematic because this plot was used to describe statistical trends directly to the general public. The results provide deceiving information that creates false narratives around a topic. These false correlations often leave the general public very confused and searching for answers regarding the significance of causation and correlation. As we can see, the X axes here start from 590 instead of zero. Using the wrong graph 7. Statistics are infamous for their ability and potential to exist as misleading and bad data. What if the measured variables were different? (, Adults Statistical Literacy: Meaning, Components, Responsibilities, National Governors Association Center for Best Practices & Council of Chief State School Officers. 5 Howick Place | London | SW1P 1WG. 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. Intermediate data points should also be identified and context is given if it would add value to the information presented. Manipulating the Y-axis+ 6. 73.6% of statistics are false. Misinformation is information that is false, inaccurate, or misleading according to the best available evidence at the time. This is an open access article distributed under the terms of the Creative Commons CC BY license, which permits unrestricted use, distribution, reproduction in any medium, provided the original work is properly cited. 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 . Developed in collaboration with the Office of Evaluation Sciences (OES). It is also worth noting that, as there is a large degree of variability within the climate system, temperatures are typically measured with at least a 30-year cycle. Incentivize coordination across grantees to maximize reach, avoid duplication, and bring together a diversity of expertise. When creating a graph to portray a statistic, it is natural to assume that the X and Y axes start at zero. 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. Figure 1, from the Healthgrades site, shows the results for the first. 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. 1. Drinking tea increases diabetes by 50%, and baldness raises the cardiovascular disease risk up to 70%! Registered in England & Wales No. Cherry Picking 2. Omitting the baseline. In 2012, the global mean temperature was measured at 58.2 degrees. As businesses are often forced to follow a difficult-to-interpret product roadmap, statistical methods can help with the planning that is necessary to navigate a landscape filled with potholes, pitfalls . False or misleading information is causing people to make decisions that could have dangerous consequences for their health. Small samples underrepresent your target audience. Dietary supplement businesses frequently exaggerate the health benefits of their products. Next, in our list of bad statistics examples, we have the case of a popular toothpaste brand. Whether this person notices or not, they might be providing an inaccurate or manipulated picture to confirm a specific conclusion. If all this is true, what is the problem with statistics? Likewise, what are the motives behind it? We can all benefit from taking steps to improve the quality of health information we consume. Proactively engage with patients and the public on health misinformation, Use technology and media platforms to share accurate health information with the public. You can be the judge. 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. It was this unethical and misleading graph, which was also FDA approved, that helped in initiating one of the biggest health crises in the US, opioid addiction. 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 2009 investigative survey by Dr. Daniele Fanelli from The University of Edinburgh found that 33.7% of scientists surveyed admitted to questionable research practices, including modifying results to improve outcomes, subjective data interpretation, withholding analytical details, and dropping observations because of gut feelings. newrepublic.com / Via reddit.com Advertisement 3. 1. That said, a bigger sample size is always better, as it highlights statistical differences more accurately. Lets put this into perspective with an example of the misuse of statistics in advertising. It is a data mining technique where extremely large volumes of data are analyzed for the purpose of discovering relationships between different points. 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. The cases start growing rapidly, but since March 26, the growth seems to slow down and come closer to the top of the curve. 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. Finally, how big was the sample set, and who was part of it? 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. Listen with empathy, ask questions, provide alternative explanations, and dont expect success from one conversation. 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. Statistical studies can also assist in the marketing of goods or services, and in understanding each target markets unique value drivers. In this case, it can create the wrong idea of a product being healthier than it actually is. Doing a quick research, you find that 900 out of 1000 patients that went into surgery at Hospital A survived, while 800 out of 1000 survived at Hospital B. By closing this message, you are consenting to our use of cookies. Omitting data 10. 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. Global Warming out of Control! 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. Misinformation is information that is false, inaccurate, or misleading according to the best available evidence at the time. The power of words is huge, therefore, carefully looking at the way a study is written is another great practice to assess its quality. Bias is most likely to take the form of data omissions or adjustments to prove a specific point. 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. Misleading Coronavirus graphs. First of all, this plot was created for use by the Kansas Department of Health and Environment, and it was showcased during an August 5 press conference (video is available here on their Facebook page), and then this plot and the description of what it means was picked up and amplified by multiple news media organizations. Continue to modernize public health communications. 3 Tweet on May 16 by Calling Bullshit showing a misleading plot produced by the Georgia Department of Public Health. Fig. These two questions are likely to provoke far different responses, even though they deal with the same topic of government assistance. Another common misuse of statistics is strategically picking the time period to show a result. Misleading graphs are a source of misinformation that worry many experts. If you perform a quantitative analysis, sample sizes under 200 people are usually invalid. As you saw throughout this post, illustrated with some insightful bad statistics examples, using data in a misleading way is very easy. Now, if the issue here is not obvious enough, we can see that the Y-axis in this chart starts from 58% and ends at 78%, making the 12% drop from 2009 to 2019 look way more significant than it actually is. Strengthen the monitoring of misinformation. 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? 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 coursework. In addition to our cases motivating discussion of association, the plots also offer an important consideration of how scaling modifications can mislead the consumer. More than half of all suicides in 2021 - 26,328 out of 48,183, or 55% - also involved a gun, the highest percentage since 2001. 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. Now, you might be wondering, how can this be misleading? Especially people with a low graph literacy are thought to be persuaded by graphs that misrepresent the underlying data. This is a Simpsons Paradox at its finest, and it happens when the data hides a conditional variable that can significantly influence the results. 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. 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. However, more often than not, data dredging is used to assume the existence of relationships without further study. 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. We all need access to trusted sources of information to stay safe and healthy. By Bernardita Calzon in Data Analysis, Jan 6th 2023, 3) Misleading Statistics Examples In Real Life. For example, a misleading data visualization included in a financial report could cause investors to buy or sell shares of company stock. The size of India's middle class is 300 million people. But, what about causation? Cumulative VS. Effects related to COVID-19 During the pandemic, health misinformation has led people to decline vaccines, reject public health measures, and use unproven treatments. 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. organization in the United States. It is fixed". 1) Misleading Data Visualization Examples 2) How to Avoid Misleading Visuals 3) The Impact Of Bad Data Visualizations Nobody likes feeling manipulated in any way, shape, or form. 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. 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. Average monthly temperature in New Haven, CT. 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). Providing solely the percentage of change without the total numbers or sample size will be totally misleading. And now have a look at the trend from 1900 to 2012: While the long-term data may appear to reflect a plateau, it clearly paints a picture of gradual warming. For instance, showing a value for 3 months can show radically different trends than showing it over a year. Lets look at one of them closely. The image below is a great example of this misleading practice. 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. Omitting the baseline 5. This list of misleading statistics fallacy examples would not be complete without referencing the COVID-19 pandemic. 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. To the question "can statistics be manipulated? Prioritize protecting health professionals and journalists from online harassment. Some useful questions to ask could be: What purpose might the Georgia Department of Public Health have had in manipulating the plot in this way? Cherry picking data. Remember, misuse of statistics can be accidental or purposeful. 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. To get this trip started, let's look at a fallacious statistics definition. Engage with your friends and family on the problem of health misinformation. Going against convention 8. Which saw an increase of millions of visitors in just a couple of years, so far, everything looks normal. 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. Citation2020; GAISE College Report ASA Revision Committee Citation2016), in particular as it relates to being a critical consumer of statistics. What Is A Misleading Statistic? Sears' Bamboo fabric > Parent Company: Sears > Ad changed: yes > Settlement Amount: $475,000 Sears Holdings agreed to pay $475,000 and. If youre not sure, dont share. Source #1: A small sample size. 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 . Quasi-experimental, single-center, before and after studies are enthusiastically performed. Learn how to identify and avoid sharing health misinformation. Truncating axes means doing the opposite. 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. 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. 19 Most Misleading Statistics (That Are Technically Correct) By: Cracked Plasticians April 20, 2016 Advertisement When the math adds up, the numbers never lie. 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 Misinformation spreads especially easily on social media and online retail sites, as well as via search engines. This is an absolute reduction of 1.2% over 4 years, or 0.3% annually. At a glance, the chart makes you believe that The Times has twice as many full-price subscriptions as its competitor. 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 . See typical methods & real-world examples of misuse of statistics the news, advertising, science & media. Establish quality metrics to assess progress in information literacy. 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.
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