Final answer:
The statement is false; multiple regression is used when the dependent variable is affected by more than one independent variable, not just one. For a single independent variable, simple linear regression is appropriate.
This corrct answer b. False
Step-by-step explanation:
The statement that multiple regression can be useful to assess cost behaviour when the dependent variable is affected by only one independent variable is false. Multiple regression is a statistical technique used when we want to predict the value of a variable based on the value of two or more other variables. In other words, multiple regression is used when the dependent variable is affected by more than one independent variable. If the dependent variable is affected by only one independent variable, simple linear regression would be the appropriate technique.
As for the practical example, if we're using the variable size as the independent variable and cost as the dependent variable, we would:
-
- Draw a scatter plot to visualize the relationship between the two variables.
-
- Calculate the least-squares line of the form ŷ = a + bx.
-
- Find the correlation coefficient to determine the strength and direction of the linear relationship between variables.
-
- Assess if the correlation is statistically significant, which would indicate a reliable linear relationship between the variables.
For example, here's how you might answer a scenario based on the given data:
-
- The independent variable is the size and the dependent variable is the cost.
-
- Based on the regression analysis, we can predict the total cost of supplies for a person living a certain distance from campus.