Question

1.) What is the difference between a simple regression model and a multiple regression model?

a.) There isn’t one. The two terms are equivalent

b.) A simple regression model has a single predictor whereas a multiple regression model has potentially many

c.) A simple regression model can handle only limited amounts of data whereas a multiple regression model can handle large data sets

d.) A simple regression is appropriate for a dichotomous outcome variable, whereas a multiple regression model should be used with a continuous outcome

2.) A simple regression models which function of the outcome variable (Y)?

a.) It models the mean of the outcome as a function of X

b.) It models the standard deviation of the outcome as a function of X

c.) It models the median of the outcome

d.) It models the variance of the outcome as a function of X

Answer 1

1. Correct Answer: b.) A simple regression model has a single predictor whereas a multiple regression model has potentially many.

>Simple linear regression: Y=b0+b1X+e, where x=predictor

>Multiple linear regression: Y=b0+b1X1+b2X2+.......+bnXn+e

X1,X2,......,Xn=predictors

e=random error

2. Correct Answer: a.) It models the mean of the outcome as a function of X.

> Simple linear regression: Y=b0+b1X+e, where e=random error.

Mean of the outcome, E(Y)=b0+b1X, which is a function of x.