Regression
Build predictive models
Regression
Regression models predict outcomes based on input variables. StatKit supports linear and logistic regression.
Types of Regression
Linear Regression
Predict continuous outcomes.
Example: Predict house prices based on size, location, age.
Logistic Regression
Predict binary outcomes.
Example: Predict whether a customer will buy (yes/no) based on demographics.
Data Requirements
Linear Regression
- Dependent Variable: Continuous numeric outcome
- Independent Variables: One or more numeric predictors
- Sample Size: At least n+1 observations (where n = number of predictors)
Logistic Regression
- Dependent Variable: Binary or categorical with exactly 2 values
- Independent Variables: One or more numeric or categorical predictors
- Sample Size: At least n+1 observations per category
How to Run
- Select “Regression” from the test dropdown
- Choose your CSV file
- Select your dependent variable
- Choose independent variables
- Click “Run Test”
Interpreting Results
Linear Regression
- R-squared: Proportion of variance explained (0 to 1)
- RMSE: Root Mean Square Error - prediction accuracy
- Coefficients: Change in outcome per unit change in predictor
- P-values: Statistical significance of predictors
Logistic Regression
- Pseudo R-squared: Measure of model fit
- Coefficients: Change in log-odds per unit change in predictor
- P-values: Statistical significance of predictors
Model Fit
- Linear: Higher R-squared indicates better fit
- Logistic: Higher pseudo R-squared indicates better fit
- P-values: < 0.05 indicates significant predictors
Assumptions
Linear Regression
- Linearity: Relationship between variables is linear
- Independence: Observations are independent
- Homoscedasticity: Constant variance of residuals
- Normality: Residuals are normally distributed
Logistic Regression
- Independence: Observations are independent
- No multicollinearity: Predictors are not highly correlated
- Large sample size: At least 10 events per predictor
Export Options
- LaTeX: Copy-paste ready tables
- CSV: Structured data files
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