Ten Common Statistical Mistakes
IN THIS CHAPTER
Recognizing common statistical mistakes
How to avoid these mistakes when doing your own statistics
This book is not only about understanding statistics that you come across in your job and everyday life; it’s also about deciding whether the statistics are correct, reasonable, and fair. After all, if you don’t critique the information and ask questions about it, who will? In this chapter, I outline some common statistical mistakes made out there, and I share ways to recognize and avoid those mistakes.
Many graphs and charts contain misinformation, mislabeled information, or misleading information, or they simply lack important information that the reader needs to make critical decisions about what is being presented.
Pie charts are nice for showing how categorical data are broken down, but they can be misleading. Here’s how to check a pie chart for quality:
- Check to be sure the percentages add up to 100%, or close to it (any round-off error should be small).
- Beware of slices labeled “Other” that are larger than the rest of the slices. This means the pie chart is too vague.
- Watch for distortions with three-dimensional-looking pie charts, in which the slice closest to you looks larger ...