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
- ANOVA with Unequal Sample Sizes
- Antecedent Variables
- Ascertainment Bias
- Assumptions of Chi-Square Test
- Assumption of Equal Variance
- Assumption of Independence
- Assumption of Normality
- Assumptions of ANOVA
- Assumptions of MANOVA
- Assumptions of Linear Regression
- Assumptions of Logistic Regression
- Assumptions of Multiple Linear Regression
- Assumptions of Paired t-Test
- Assumptions of Parametric Tests
- Assumptions of Pearson Correlation
- Assumptions of Repeated Measures ANOVA
- Assumptions of t-Test
- Attributable Risk
B
- Back to Back Stem-and-Leaf Plots
- Balanced Accuracy
- 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 Distribution Assumptions
- 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
- Calculate Percentile from Mean & Standard Deviation
- Can a Z-Score Be Negative?
- Can Kurtosis Be Negative?
- Can Variance Be Negative?
- Carryover Effects
- Cases in Statistics
- Categorical Distribution
- Categorical vs. Quantitative Variables
- Ceiling Effects
- Central Tendency Bias
- Chi-Square Test by Hand
- Chi-Square Test vs. t-Test
- Chi-Square Test vs. ANOVA
- Choosing Which Variable to Place on X-Axis and Y-Axis
- 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
- Complete Guide: The 2×3 Factorial Design
- Conceptual Variable
- Concomitant Variables
- Concurrent Validity
- Conditional Distribution
- Conditional Relative Frequency in a Two-Way Table
- Conditions of the Central Limit Theorem
- Confidence Interval for Odds Ratio
- Confidence Interval for Relative Risk
- Confidence Interval for a Regression Intercept
- Confidence Interval Using the F Distribution
- Confidence Interval Assumptions
- Confidence Interval vs. Prediction Interval
- Confidence Level vs. Confidence Interval
- Confidentiality vs Anonymity
- Confounding Variable
- Constant Variance Assumption
- Content Validity
- Continuity Correction
- Convert Z-Scores to Raw Scores
- Correlation Between Categorical Variables
- Correlation vs. Association
- Correlation vs. Regression
- Covariance vs. Variance
- Covariates
- Criterion Validity
- Criterion Variable
- Cross-Lagged Panel Design
- Curvilinear Regression
D
- Decision Trees vs. Random Forests
- Determine Equal or Unequal Variance in t-tests
- Detrending Data
- Dichotomous Variables
- Differences Between ANOVA, ANCOVA, MANOVA, and MANCOVA
- Directional Hypothesis
- Disjoint Events
- Disjoint vs. Independent Events
- Dixon’s Q Test for Outliers
- Does Causation Imply Correlation?
- Dot Plot vs. Histogram
- 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 Bivariate Data in Real Life
- Examples of Central Limit Theorem in Real Life
- Examples of Chi-Square Tests in Real Life
- Examples of Cluster Analysis in Real Life
- Examples of Confidence Intervals in Real Life
- Examples of Correlation Does Not Imply Causation
- Examples of Correlation in Real Life
- Examples of Expected Value 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 Outliers in Real Life
- Examples of Positively Skewed Distributions
- Examples of Probability in Real Life
- Examples of Negatively Skewed Distributions
- Examples of Random Variables in Real Life
- Examples of Standard Deviation in Real Life
- Examples of How Statistics is Used in Real Life
- Examples of T-Tests in Real Life
- Examples of Time Series Analysis in Real Life
- Examples of the Binomial Distribution in Real Life
- Examples of the Exponential 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
- Examples of Z-Scores in Real Life
- Expected Frequency
- Expected Value vs. Mean
- Extraneous Variables
F
- F1 Score vs. Accuracy
- Face Validity
- Factorial ANOVA
- Family-wise Error Rate?
- Find Area to the Left of Z-Score
- Find Area to the Right of Z-Score
- Find Average of Several Standard Deviations
- Find Center and Spread of a Dot Plot
- Find Outliers Using the Interquartile Range
- Find Probability Given a Mean and Standard Deviation
- Find Quartiles Using Mean and Standard Deviation
- Find Z-Scores Given Area
- Finite Population Correction Factor
- Fisher’s Least Significant Difference
- Fisher Z-Transformation
- Floor Effects
G
H
- Hedges’ g
- High Dimensional Data
- How Do Outliers Affect the Mean?
- How to Interpret a Confidence Interval that Contains Zero
- How to Interpret Cramer’s V
- How to Interpret the F-Value and P-Value in ANOVA
- 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 Relative Risk
- How to Interpret Residual Standard Error
- How to Interpret Root Mean Square Error (RMSE)
- How to Read a Correlation Matrix
- How to Read a Semi-Log Graph
- How to Report Chi-Square Results
- How to Report Confidence Intervals
- How to Report Cronbach’s Alpha
- How to Report Fisher’s Exact Test 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 Logistic Regression Results
- How to Report Odds Ratios
- How to Report Pearson’s Correlation
- How to Report Regression Results
- How to Report Skewness & Kurtosis
- 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 Confidence Interval Conclusion
- How to Write a Hypothesis Test Conclusion
- How to Write a Null Hypothesis
I
- i.i.d. Random Variables
- Importance of the Median
- Importance of Sample Size
- Importance of Standard Deviation
- Incidence Rate Ratio
- Inference vs. Prediction
- Influential Observation
- Instrumental Variables
- Intercept in Regression Model
- Internal Consistency
- Interpolation vs. Extrapolation
- Interpreting Cohen’s d
- Interpreting Log-Likelihood Values
- Interpreting Null & Residual Deviance
- Interpreting P-Values Less Than 0.05
- Interpreting P-Values Equal to 0.000
- Interpreting ROC Curves
- 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 Age a Qualitative or Quantitative Variable?
- Is Age An Interval or Ratio Variable?
- Is Time An Interval or Ratio 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
- Likelihood vs. Probability
- Ljung-Box Test
- Logistic Regression vs. Linear Regression
- Long vs. Wide Data
- 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)
- Mauchly’s Test of Sphericity
- Maximum Variation Sampling
- Mean Absolute Deviation vs Standard Deviation
- Mean of a Probability Distribution
- Mean & Standard Deviation of Grouped Data
- Memoryless Property
- Minimum Sample Size for a t-test
- MLE for a Uniform Distribution
- MLE for a Poisson Distribution
- Moderating Variable
- Modified Z-Score
- Monotonic Relationship
- Moran’s I
- MSE vs. RMSE
- 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
- Nested Model
- 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
- Odds Ratio vs. Relative Risk
- Omitted Variable Bias
- Omnibus Test
- One-Sided Confidence Intervals
- 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
- Parameter of Interest
- Pareto Chart vs. Histogram
- Parsimonious Model
- Partial Eta Squared
- Partial F-Test
- Partial Regression Coefficient
- Pearson Correlation Coefficient
- Pearson Residuals
- Percentile vs. Quartile vs. Quantile
- Percentile Rank for Grouped Data
- Perfect Multicollinearity
- Phi Coefficient
- Pillai’s Trace
- Point Estimate
- Poisson Confidence Interval
- Poisson Distribution Assumptions
- Poisson vs. Normal Distribution
- Pooled Standard Deviation
- Pooled Variance
- Population Proportion
- Population vs. Sample Standard Deviation
- Prediction Error
- 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
- Probability vs. Proportion
- Pseudoreplication
Q
R
- R vs. R-Squared
- Rand Index
- Randomization
- Range Rule of Thumb
- Range vs. Standard Deviation
- Random Selection vs. Random Assignment
- Raw Data
- Rayleigh Distribution
- Referral Bias
- Regression Through the Origin
- Regressor
- Relative Frequency Distribution
- Reliability Analysis
- Residuals
- Residuals in ANOVA
- Residuals vs. Leverage Plot
- Residual Plot: How to Create by Hand
- Residual Variance
- Resistant Statistic
- Restriction of Range
- Reverse Causation
- Reverse Coding
- RMSE vs. R-Squared
- RMSE vs. MAE
S
- Sample Mean vs. Population Mean
- Sample Mean vs. Sample Proportion
- Sample Size and Margin of Error
- Sample Space
- Sample Variance vs. Population Variance
- Sampling Variability
- Sampling With Replacement vs. Without Replacement
- Satterthwaite Approximation
- Segmented Bar Chart
- Self-Selection Bias
- Sequence Effects
- Shannon Diversity Index
- Shape of Histograms
- Simpson’s Diversity Index
- Skewness in Box Plots
- Snowball Sampling
- Somer’s D
- Spearman-Brown Formula
- 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 Regression Slope
- 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-Score vs. Z-Score
- t-Test for Correlation
- t-Test in Linear Regression
- T-Value vs. P-Value
- Test-Retest Reliability
- Tetrachoric Correlation
- The 10% Condition
- Third Variable Problem
- Treatment Diffusion
- Triangular Distribution
- Trimmed Mean
- Truncated & Censored Data
- Tukey vs. Bonferroni vs. Scheffe
- Two-Stage Cluster Sampling
- Types of Logistic Regression
- Types of Regression
U
- Undercoverage Bias
- Understanding the Null Hypothesis for Linear Regression
- Understanding the Null Hypothesis for Logistic 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 AUC Score?
- What is Considered a Good Confidence Interval?
- What is Considered a Good Value for MAPE?
- What is Considered a Good Coefficient of Variation?
- What is Considered a Good F1 Score?
- 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 Remove Outliers in Data
- When to Use a Chi-Square Test
- When to Use Box Plots
- When to Use Correlation
- When to Use Log Scale
- When to Use Mean vs. Median
- When to Use Polynomial Regression
- When to Use Ridge & Lasso Regression
- Winsorize Data
- Within-Group vs. Between Group Variation in ANOVA