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. Misleading Statistics Examples In Healthcare Misleading statistics are dangerous. Educate students and the public on common tactics used by those who spread misinformation online. Data Sources for Health Care Quality Measures Statistical analyses have historically been a stalwart of the high-tech and advanced business industries, and today they are more important than ever. 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. Each kind is calculated differently and gives different information (and a different impression) about the data: It would be preposterous to say that they cause each other and that is exactly why it is our example. 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). If you really want to make a shocking statement, make sure you only include part of the data. Three Misleading, Dangerous Coronavirus Statistics The Govenor race where one guy's 37% was WAY more than just 37% gravismarketing.com / Via reddit.com 4. 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. Misuse of Statistics- What Leads to The Misuse of Statistics 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. 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 Establish quality metrics to assess progress in information literacy. 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. Duo writes about how health statistics can mislead 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.