PSYC 3070K - Quantitative Methods: Linear Regression

These flashcards cover key vocabulary and concepts related to linear regression, focusing on definitions and essential terms that are foundational for understanding the topic.

Linear Regression

A statistical method for modeling the relationship between a dependent variable (criterion variable) and one or more independent variables (predictor variables).

Criterion Variable

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

Predictor Variable

The variable used to predict the outcome of the criterion variable.

Prediction Errors (Residuals)

The differences between observed values and the predicted values in a regression analysis.

Standard Error of Estimate

A measure of the accuracy of predictions made with a regression line, representing the standard deviation of the prediction errors.

Sum of Squares (SSY)

A measure of variability that sums the squared deviations of each data point from the mean.

R-squared (R²)

The proportion of variance in the criterion variable that is explained by the predictor variables in a regression model.

Simple Linear Regression

A type of linear regression that uses one predictor variable to predict a criterion variable.

Slope (b)

The coefficient that indicates the degree of change in the criterion variable for a one-unit change in the predictor variable.

y-intercept (A)

The constant term in the regression equation representing the expected value of the criterion variable when the predictor variable is zero.

Standardized Coefficient (β)

A regression coefficient computed based on standard deviations rather than the original units of measurement.

Unstandardized Coefficient (b)

A regression coefficient derived from the original units of the predictor variable.

ANOVA (Analysis of Variance)

A statistical method used to determine if there are statistically significant differences between the means of three or more independent (unrelated) groups.

Regression Coefficients

The values that represent the magnitude and direction of the relationship between predictor variables and the criterion variable.

Correlation Coefficient (r)

A measure that indicates the extent to which two variables fluctuate together.

Best-Fitting Line

The line that minimizes the sum of squared prediction errors in a regression analysis.

Z-scores

Standardized scores indicating how many standard deviations an element is from the mean.