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COMMON MISTEAKS MISTAKES IN USING STATISTICS: Table of Contents

Introduction

Types of mistakes

Expecting too much certainty
What is probability?
More quotes about uncertainty
Terminology: Variation, Variability, and Uncertainty

Misunderstandings about probability
Misunderstandings arising from different perspectives on probability
Misunderstandings arising from lack of clarity about the reference category
Misunderstandings involving different uses of the word "risk"
Misunderstandings involving conditional probabilities

Mistakes in thinking about causation

Problematical choice of measure
Choosing an outcome variable
Wording questions
Elaboration
Suggestions
Choosing a summary statistic
Skewed distributions
Unusual events
Distributions with large variability

Errors in sampling
What is a Random Sample: Sources of Confusion
Simple Random Samples
More Precise Definition of Simple Random Sample
Random Variables and Probability Distributions
Other Types of Random Samples
Why is random sampling important?
Overview of Frequentist Hypothesis Testing
Biased sampling and Extrapolation

Over-interpretation
Extrapolation Beyond the Range of Data

Mistakes involving limitations of hypothesis tests/confidence intervals
Overview of Frequentist Confidence Intervals
Summary Chart and Diagram for Original Distribution and Sampling Distribution for Confidence Interval
Overview of Frequentist Hypothesis Tests
Frequentist Hypothesis Tests and  p-values 
Misinterpretations of p-values
Type I and Type II Errors
Choosing Confidence Levels for Confidence Intervals
Mistakes Involving Power    Expanded and revised May 12, 2011
Power of a Statistical Procedure
Factors that Affect Power
Power and Sample Size
Detrimental Effects of Under-powered or Over-powered Studies
Common Mistakes Involving Power
The File Drawer Problem (Publication Bias)
Example of How Low Power and Publication Bias Interact    New May 12, 2011
Multiple Inference
Data Snooping

Using an inappropriate model or research design
Checking Model Assumptions Using Well-Established Facts or Theorems
Using Plots to Check Model Assumptions
Using a two-sample test comparing means when cases are paired (also includes discussion of repeated measures)
Comparisons of treatments applied to people, animals, etc.  (Intent to Treat; Comparisons with Drop-Outs)
Fixed vs Random Factors
Analyzing Data without Regard to How the Data Were Collected 
Dividing a Continuous Variable into Categories ("Chopped Data")
Pseudoreplication
Mistakes in Regression
Overfitting
Conditional Distributions
Misinterpreting the Overall F-Statistic in Regression
Using Confidence Intervals when Prediction Intervals Are Needed
Overinterpreting high R2
Mistakes in Interpretation of Coefficients
Interpreting a Coefficient as a Rate of Change in Y Instead of as a Rate of Change in the Conditional Mean of Y
Mistakes in Selecting Terms
Assuming Linearity is Preserved when Terms are Dropped
Problems with Stepwise Model Selection Procedures

Inadequate attention to communication

Suggestions for reducing the incidence of mistakes in using statistics

Glossary

Further resources

Table of Contents

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Last updated April 10, 2012