# Misleading Statistics: Definition & Examples

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• 0:02 Definition of…
• 1:02 The Beginning/Misinformation
• 1:54 Neglecting the Baseline
• 2:18 Fallacious Comparisons
• 3:47 Lesson Summary

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Lesson Transcript
Instructor: Karin Gonzalez

Karin has taught middle and high school Health and has a master's degree in social work.

In this lesson, you'll learn the definition of misleading statistics, including the different types and how to spot them. You'll also explore some hypothetical examples and have the chance to see how well you absorbed the material with a brief quiz.

Statistics is the practice of collecting, organizing, and representing large amounts of numerical data. Statistics can tell us about trends that are happening in the world.

For example, statistics can tell us how many people had cancer ten years ago as opposed to today. If more people have cancer now, the figure may prompt more research to see what is causing this upward trend. Research can lead to discoveries of why cancer has increased and theories on how it can be prevented and treated. Now do you see why statistics are so important? Much of our knowledge about our world is based on information gathered from statistics!

Misleading statistics, on the other hand, is a term that refers to the misusage of numerical data, either intentionally or due to error, that results in misleading information. Misleading statistics can deceive the receiver of the information if the receiver is not careful to notice the error or deception. Statistics can be misleading in a number of ways. In this lesson, we'll discuss four different ways: inventing false statistical information, misinformation, neglecting the baseline, and making fallacious comparisons.

## The Beginning

One of the most basic forms of misleading statistics occurs when someone makes up a statistic. Let's pretend that Mary is an advocate for reducing world hunger. While speaking to a large group of potential donors to her organization, she states that there are a billion people in the world who are hungry. In reality, Mary does not know the exact number of hungry people on Earth, but she thinks that 'a billion' will make her cause sound more important. However, the amount of hungry people is more around 795 million.

## Misinformation

A 1998 publication in the real-life journal, The Lancet, claimed that the vaccination for measles, mumps, and rubella for babies was causing an increase in autism. It was later confirmed that the journal author falsified the findings. Unfortunately, this statistical misinformation led to a surge of people who were afraid to immunize their babies, which led to an increase in diagnoses of measles across the United States.

## Neglecting the Baseline

Let's pretend that the mayor of Pleasantown reports that his town has less crime than the major metropolitan city of Miapolis. However, by ignoring the baseline in his statistic, the mayor doesn't account for the fact that Miapolis has many more people than Pleasantown. So, of course, that city has more crime! As a more accurate alternative, the mayor could report the crime per capita for his town, which is the number of crimes divided by the total number of people in a population.

## Fallacious Comparisons

Consider the hypothetical drug, Deprita, which was created to help treat depression. In a research study, the drug's manufacturers compared the levels of depression found among members of a depression support group before they started taking Deprita and six weeks after taking the drug. According to the results, members of the support group were much less depressed at the end of the 6-week trial period.

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