Statistics - Regression

Regression

Predicting a dependent variable based on independent variable.

Simple regression

Predicting a dependent variable from one independent variable.

Multiple regression

Predicting a dependent variable from more than one independent variable.

Dependent variable

The variable that is predicted or explained in a regression model.

Independent variable

The variable that is used to predict the dependent variable.

Regression coefficient (b)

A value that represents the degree of change in the dependent variable for a one-unit change in the independent variable.

Homoscedasticity

The condition of having constant variance of residuals in a regression model.

Null hypothesis (H0)

The hypothesis that there is no significant effect or relationship in the population.

Research hypothesis (H1)

The hypothesis that there is a significant effect or relationship in the population.

ANOVA table

A table that summarizes the variation between groups and tests the hypothesis.

Q-Q plot

A graphical tool to assess if a dataset follows a normal distribution.

Durbin-Watson statistic

A test statistic used to detect the presence of autocorrelation in the residuals from a regression analysis.

Outliers

Data points that differ significantly from other observations and may affect the results of regression analysis.

Linear equation

An equation that models the relationship between a dependent variable and one or more independent variables using a linear function.

Interpretation of R²

This value indicates the proportion of variance in the dependent variable that is predictable from the independent variable(s).

Scatter plot

A graphical representation that displays the relationship between two quantitative variables.

Regression equation

The mathematical expression that predicts the dependent variable based on independent variable(s).