Least Squares Regression

Flashcards covering key concepts from the Least Squares Regression lecture.

Least Squares Regression Line (LSRL)

A linear model that minimizes the sum of squared residuals.

Residuals

The difference between observed values and the values predicted by a regression model.

Sum of Squared Residuals

The total of the squares of the residuals, used to determine the best-fit line in regression analysis.

Correlation

A statistical measure that expresses the extent to which two variables are linearly related.

Explanatory Variable

The independent variable that is used to predict the response variable.

Response Variable

The dependent variable that is being predicted in a regression analysis.

X-bar (x̄)

The mean of the x-values in a dataset.

Y-bar (ȳ)

The mean of the y-values in a dataset.

Slope of the LSRL

Calculated using the correlation coefficient and the standard deviations of the response and explanatory variables.

Standard Deviation

A measure of the amount of variation or dispersion in a set of values.