This page provides a glossary of all statistics terms and concepts available on Statology.

**A**

- Aggregation Bias
- Antecedent Variables
- Assumptions of ANOVA
- Assumptions of Linear Regression
- Assumptions of Logistic Regression

**B**

- Benjamini-Hochberg Procedure
- Bimodal Distributions
- Binomial Experiments
- Bivariate Analysis
- Blocking
- Brier Score

**C**

- C-Statistic of a Logistic Regression Model
- Calculate a Pearson Correlation Coefficient by Hand
- Can a Z-Score Be Negative?
- Can Kurtosis Be Negative?
- Ceiling Effects
- Chi-Square Test vs. t-Test
- Class Midpoints
- Comparing Z-Scores from Different Distributions
- Concomitant Variables
- Conditional Relative Frequency in a Two-Way Table
- Confidence Interval Using the F Distribution
- Confidentiality vs Anonymity
- Continuity Correction
- Covariates
- Criterion Variable

**D**

**E**

- Extraneous Variables
- Empirical Rule Practice Problems
- Examples of ANOVA in Real Life
- Examples of Linear Regression in Real Life
- Examples of Logistic Regression in Real Life
- Expected Frequency

**F**

**H**

**I**

- Instrumental Variables
- Internal Consistency
- Intervening Variables
- Is the Interquartile Range (IQR) Affected By Outliers?

**K**

**L**

**M**

- Margin of Error vs. Standard Error
- Matrix Multiplication: (2×2) by (2×2)
- Matrix Multiplication: (2×2) by (2×3)
- Matrix Multiplication: (3×3) by (3×2)
- Maximum Variation Sampling
- MLE for a Uniform Distribution
- MLE for a Poisson Distribution
- Multinomial Coefficient

**N**

- Neyman Bias
- Nonresponse Bias
- Normal Distribution vs. t-Distribution
- Normalize Data Between 0 and 100

**O**

**P**

- Parsimonious Model
- Pearson Correlation Coefficient
- Phi Coefficient
- Pooled Standard Deviation
- PRESS Statistic
- Pseudoreplication

### R

**S**

- Sample Mean vs. Population Mean
- Standard Deviation vs. Standard Error
- Snowball Sampling
- Split-Half Reliability
- Standardized Test Statistic
- Standardized vs. Unstandardized Regression Coefficients
- Success/Failure Condition

**T**

**U**

**W**

- What is a Good R-squared Value?
- What is Considered to Be a Strong Correlation?
- What is the Difference Between a T-test and an ANOVA?