Regression coefficient
The regression coefficient is a term used in linear regression analysis that represents the strength and direction of the relationship between a dependent variable and one or more independent variables. It measures how much the dependent variable is expected to change for a one-unit change in the independent variable, holding all other variables constant. The coefficient indicates the slope of the regression line, with positive coefficients indicating a positive relationship and negative coefficients indicating a negative relationship.
Give an example
Sure! Let's say we are conducting a linear regression analysis to examine the relationship between the number of study hours (independent variable) and exam scores (dependent variable) of college students.
After running the regression model, we find that the regression coefficient for the number of study hours is 0.5. This means that for every additional hour of study time, the exam score is expected to increase by 0.5 points, assuming all other factors remain constant.
Therefore, a regression coefficient of 0.5 suggests a positive linear relationship between study hours and exam scores, indicating that increasing study hours is associated with higher exam scores.