Linear Regression and Correlation

These flashcards cover key concepts and terms related to linear regression, correlation, and their calculations.

Linear Regression

A statistical method used to model the relationship between a dependent variable and one or more independent variables by fitting a linear equation to observed data.

Line of Best Fit

A line that best represents the data on a scatter plot, indicating the general direction that a group of points seems to follow.

Slope (b)

The measure of the steepness of the line in the regression equation; it indicates how much the dependent variable changes with a unit change in the independent variable.

Y-Intercept (a)

The value of the dependent variable when the independent variable is zero; it is the point where the line crosses the y-axis.

Correlation Coefficient (r)

A statistical measure that indicates the strength and direction of the relationship between two variables, ranging from -1 to 1.

Positive Correlation

A relationship between two variables in which an increase in one variable tends to be associated with an increase in the other variable.

Negative Correlation

A relationship between two variables in which an increase in one variable tends to be associated with a decrease in the other variable.

Least Squares Regression

A method to find the best-fitting line by minimizing the sum of the squares of the vertical distances of the points from the line.

Scatter Plot

A graph that displays values for typically two variables for a set of data, using points to represent the values.

Causation vs. Correlation

The principle that correlation between two variables does not imply that one causes the other.