14.3: Model Assumptions and the Standard Error Flashcards
What is assumed about the error term in simple linear regression?
It’s assumed that the error term has a mean of zero for any given value of the independent variable x, which indicates that there’s no inherent bias in the error terms.
What is the constant variance assumption in simple linear regression?
The constant variance assumption means that the spread or variance of the error term is the same across all values of the independent variable, also known as homoscedasticity.
What is the normality assumption regarding the error terms in regression?
The normality assumption postulates that for any given value of x, the error terms are normally distributed, which supports the validity of various statistical tests.
What is the independence assumption in the context of regression error terms?
The independence assumption implies that the error terms are statistically independent from one another, meaning the error term for one observation doesn’t affect another.
What is the simple linear regression model?
What are the least squares point estimates in simple linear regression?
How do you calculate and interpret the simple coefficients of determination and correlation?
What are the assumptions behind simple linear regression?
Simple linear regression has four main assumptions:
The mean of the error terms is zero.
The variance of the error terms is constant (homoscedasticity).
The error terms are normally distributed (normality).
The error terms are independent of each other (independence).
What is the standard error in simple linear regression?
How do you calculate the mean square error and the standard error?
How is the simple correlation coefficient calculated?
