In a linear regression model, what does the slope coefficient represent?

The intercept of the regression line
The change in the dependent variable for a one-unit change in the independent variable
The total variance in the dependent variable
The correlation between the independent and dependent variables

In a linear regression model, what does the slope coefficient represent?

Step 1: Understand that a linear regression model is used to predict a dependent variable based on one or more independent variables.
Step 2: Identify the dependent variable, which is the outcome we want to predict.
Step 3: Identify the independent variable, which is the factor we are changing to see its effect on the dependent variable.
Step 4: Look at the slope coefficient in the regression equation, which is usually represented as 'b' in the equation y = mx + b.
Step 5: Realize that the slope coefficient tells us how much the dependent variable (y) will change when the independent variable (x) increases by one unit.
Step 6: If the slope coefficient is positive, it means the dependent variable is expected to increase. If it is negative, it means the dependent variable is expected to decrease.

No concepts available.