What is the underlying assumption of linearity in a multiple linear regression model?
- All independent variables must have a linear relationship with the dependent variable
- All residuals must be equal
- All variables must be continuous
- All variables must be normally distributed
The assumption of linearity in a multiple linear regression model assumes that the relationship between each independent variable and the dependent variable is linear. This implies that the change in the dependent variable due to a one-unit change in the independent variable is constant, regardless of the value of the independent variable.
Loading...
Related Quiz
- How does the Mann-Whitney U test compare to the Wilcoxon rank-sum test?
- The Z-score and T-score are both types of _______ scores, which measure the number of standard deviations an observation is from the mean.
- How is a probability distribution defined?
- A _______ is a range of values, derived from a sample, that is used to estimate an unknown population parameter.
- What is the significance of the total probability rule?