This page provides a glossary of all statistics terms and concepts available on Statology.
A
- Adjusted Odds Ratio
- Aggregation Bias
- Alternative Hypothesis
- ANOVA vs. Regression
- Antecedent Variables
- Ascertainment Bias
- Assumption of Equal Variance
- Assumption of Independence
- Assumption of Normality
- Assumptions of ANOVA
- Assumptions of Linear Regression
- Assumptions of Logistic Regression
- Assumptions of a t-Test
- Attributable Risk
- Average Deviation
B
- Back to Back Stem-and-Leaf Plots
- Balanced vs. Unbalanced Designs
- Bartlett’s Test for Homogeneity of Variances
- Benjamini-Hochberg Procedure
- Berkson’s Bias
- Bernoulli vs Binomial Distribution
- Beta Level
- Bimodal Distributions
- Binomial Coefficient
- Binomial Experiments
- Binomial vs. Geometric Distribution
- Binomial vs. Poisson Distribution
- Bivariate Analysis
- Bland-Altman Plot
- Blocking
- Bonferroni Correction
- Bray-Curtis Dissimilarity
- Brier Score
C
- C-Statistic of a Logistic Regression Model
- Calculate P-Value from a Z-Score by Hand
- Calculate Pearson Correlation Coefficient by Hand
- Calculate R-Squared by Hand
- Calculate Mean from Frequency Table
- Calculate Median from Frequency Table
- Calculate Mode from Frequency Table
- Can a Z-Score Be Negative?
- Can Kurtosis Be Negative?
- Can Variance Be Negative?
- Carryover Effects
- Categorical Distribution
- Categorical vs. Quantitative Variables
- Ceiling Effects
- Central Tendency Bias
- Chi-Square Test vs. t-Test
- Chow Test
- Class Boundaries
- Class Intervals
- Class Limits
- Class Midpoints
- Class Size
- Cluster Sampling vs. Stratified Sampling
- Clustered Standard Errors
- Cochran’s Q Test
- Coefficient of Variation vs. Standard Deviation
- Collectively Exhaustive Events
- Comparing Box Plots
- Comparing Z-Scores from Different Distributions
- Complete Guide: The 2×2 Factorial Design
- Concomitant Variables
- Concurrent Validity
- Conditional Distribution
- Conditional Relative Frequency in a Two-Way Table
- Conditions of the Central Limit Theorem
- Confidence Interval Using the F Distribution
- Confidence Interval Assumptions
- Confidence Level vs. Confidence Interval
- Confidentiality vs Anonymity
- Confounding Variable
- Content Validity
- Continuity Correction
- Convert Z-Scores to Raw Scores
- Correlation vs. Association
- Correlation vs. Regression
- Covariance vs. Variance
- Covariates
- Criterion Validity
- Criterion Variable
- Cross-Lagged Panel Design
- Curvilinear Regression
D
- Determine Equal or Unequal Variance in t-tests
- Detrending Data
- Dichotomous Variables
- Differences Between ANOVA, ANCOVA, MANOVA, and MANCOVA
- Directional Hypothesis
- Disjoint Events
- Dixon’s Q Test for Outliers
- Dummy Variables in Regression Analysis
- Dummy Variable Trap
- Durbin-Watson Test
E
- Empirical Rule Practice Problems
- Endogenous vs. Exogenous Variables
- Erlang Distribution
- Error Propagation
- Estimating the Mean and Median of Histograms
- Eta Squared
- Examples of ANOVA in Real Life
- Examples of Confidence Intervals in Real Life
- Examples of Correlation in Real Life
- Examples of Hypothesis Testing in Real Life
- Examples of Linear Regression in Real Life
- Examples of Logistic Regression in Real Life
- Examples of Mean, Median, & Mode in Real Life
- Examples of No Correlation Between Variables
- Examples of Positively Skewed Distributions
- Examples of Negatively Skewed Distributions
- Examples of T-Tests in Real Life
- Examples of the Binomial Distribution in Real Life
- Examples of the Geometric Distribution in Real Life
- Examples of the Normal Distribution in Real Life
- Examples of the Poisson Distribution in Real Life
- Examples of the Uniform Distribution in Real Life
- Expected Frequency
- Extraneous Variables
F
- Face Validity
- Factorial ANOVA
- Family-wise Error Rate?
- Find Outliers Using the Interquartile Range
- Find Probability Given a Mean and Standard Deviation
- Find Z-Scores Given Area
- Finite Population Correction Factor
- Fisher’s Least Significant Difference
- Floor Effects
G
H
- Hedges’ g
- High Dimensional Data
- How Do Outliers Affect the Mean?
- How to Interpret Interquartile Range
- How to Interpret MAPE Values
- How to Interpret Negative AIC Values
- How to Interpret an Odds Ratio Less Than 1
- How to Interpret Residual Standard Error
- How to Interpret Root Mean Square Error (RMSE)
- How to Read a Correlation Matrix
- How to Report Chi-Square Results
- How to Report One-Way ANOVA Results
- How to Report Two-Way ANOVA Results
- How to Report Repeated Measures ANOVA Results
- How to Report Cronbach’s Alpha
- How to Report Pearson’s Correlation
- How to Report Regression Results
- How to Report Spearman’s Correlation
- How to Report T-Test Results
- How to Use Q-Q Plots to Check Normality
- How to Write a Null Hypothesis
- How to Write a Confidence Interval Conclusion
I
- Importance of the Median
- Importance of Sample Size
- Influential Observation
- Instrumental Variables
- Intercept in Regression Model
- Internal Consistency
- Interpreting P-Values Less Than 0.05
- Interpreting P-Values Equal to 0.000
- Interpreting Z-Scores
- Interquartile Range vs. Standard Deviation
- Interquartile Range of a Box Plot
- Intervening Variables
- Inter-rater Reliability
- Intraclass Correlation Coefficient
- Inverse Normal Distribution
- Is Age a Discrete or Continuous Variable?
- Is the Interquartile Range (IQR) Affected By Outliers?
J
K
L
- Large Sample Condition
- Law of Total Probability
- Left Skewed vs. Right Skewed Distributions
- Left Tailed Test vs. Right Tailed Test
- Levels of an Independent Variable
- Ljung-Box Test
- Lurking Variables
M
- Mallows’ Cp
- Manipulated Variables
- Marginal Distribution
- Marginal Mean
- Margin of Error vs. Standard Error
- Margin of Error vs. Confidence Interval
- Matrix Multiplication: (2×2) by (2×2)
- Matrix Multiplication: (2×2) by (2×3)
- Matrix Multiplication: (3×3) by (3×2)
- Maximum Variation Sampling
- Mean Absolute Deviation vs Standard Deviation
- Mean of a Probability Distribution
- Mean & Standard Deviation of Grouped Data
- Memoryless Property
- MLE for a Uniform Distribution
- MLE for a Poisson Distribution
- Moderating Variable
- Modified Z-Score
- Monotonic Relationship
- Moran’s I
- Multimodal Distribution
- Multinomial Coefficient
- Multinomial Test
- Multiple R vs. R-Squared
- Multistage Sampling
- Mutually Inclusive vs. Mutually Exclusive Events
N
- Negative Binomial vs. Poisson Regression
- Nested ANOVA
- Neyman Bias
- Nonresponse Bias
- Normal Approximation
- Normal Distribution vs. t-Distribution
- Normal Distribution vs. Standard Normal Distribution
- Normal Distribution vs. Uniform Distribution
- Normalize Data Between 0 and 1
- Normalize Data Between 0 and 100
- Number Needed to Harm
O
- Observation
- Observer Bias
- Omitted Variable Bias
- Omnibus Test
- One-Way vs. Two-Way ANOVA
- One-Way vs. Repeated Measures ANOVA
- Open Ended Distribution
- Order Effects
- Outcome vs. Event
P
- P-Value vs. Alpha
- Paired Data
- Paired vs. Unpaired t-test
- Paired t-Test by Hand
- Parallel Forms Reliability
- Parsimonious Model
- Partial Eta Squared
- Partial F-Test
- Partial Regression Coefficient
- Pearson Correlation Coefficient
- Percentile vs. Quartile vs. Quantile
- Phi Coefficient
- Pillai’s Trace
- Point Estimate
- Poisson Confidence Interval
- Poisson Distribution Assumptions
- Pooled Standard Deviation
- Pooled Variance
- Population Proportion
- Predictions with Linear Regression
- Predictive Validity
- PRESS Statistic
- Probability of A and B
- Probability of A or B
- Probability of “At Least One” Success
- Probability Distribution Table
- Probability Mass Function
- Pseudoreplication
Q
R
- R vs. R-Squared
- Rand Index
- Randomization
- Range Rule of Thumb
- Range vs. Standard Deviation
- Random Selection vs. Random Assignment
- Rayleigh Distribution
- Referral Bias
- Regressor
- Relative Frequency Distribution
- Reliability Analysis
- Residuals
- Residual Plot: How to Create by Hand
- Residual Variance
- Resistant Statistic
- Restriction of Range
- Reverse Causation
- RMSE vs. R-Squared
S
- Sample Mean vs. Population Mean
- Sample Mean vs. Sample Proportion
- Sample Space
- Sampling Variability
- Sampling With Replacement vs. Without Replacement
- Satterthwaite Approximation
- Segmented Bar Chart
- Self-Selection Bias
- Sequence Effects
- Shannon Diversity Index
- Simpson’s Diversity Index
- Skewness in Box Plots
- Snowball Sampling
- Somer’s D
- Split-Half Reliability
- Standardization vs. Normalization
- Standard Deviation of a Probability Distribution
- Standard Deviation vs. Standard Error
- Standard Error of Estimate
- Standard Error of Measurement
- Standard Error of the Proportion
- Standardized Residuals
- Standardized Test Statistic
- Standardized vs. Unstandardized Regression Coefficients
- Stanine Score
- Stem-and-Leaf Plots: How to Find Mean, Median, & Mode
- Sturges’ Rule
- Success/Failure Condition
- Sum of Squares: SST, SSR, SSE
- Symmetric Distribution
T
- t Alpha/2 Values
- t-Test for Correlation
- Test-Retest Reliability
- Tetrachoric Correlation
- The 10% Condition
- Third Variable Problem
- Treatment Diffusion
- Triangular Distribution
- Truncated & Censored Data
- Tukey vs. Bonferroni vs. Scheffe
- Two-Stage Cluster Sampling
- Types of Regression
U
- Undercoverage Bias
- Understanding the Null Hypothesis for Linear Regression
- Understanding the Shape of a Binomial Distribution
- Ungrouped Frequency Distribution
- Unimodal Distribution
- Univariate Analysis
- Upper and Lower Fences
V
W
- What Does a High F Value Mean in ANOVA?
- What is Considered a Good AIC Value?
- What is Considered a Good Value for MAPE?
- What is Considered a Good Coefficient of Variation?
- What is Considered a Good RMSE Value?
- What is Considered a Good Z-Score?
- What is Considered a Good Standard Deviation?
- What is Considered a Low Standard Deviation?
- What is Considered to Be a Strong Correlation?
- What is Considered to Be a Weak Correlation?
- What is a Good R-squared Value?
- What is the Difference Between a T-test and an ANOVA?
- When to Use a Chi-Square Test
- When to Use Mean vs. Median
- Winsorize Data