Ryan has constructed a multiple regression model and wants to test some assumptions of his regression model. In particular, he i
s testing for normality of the residuals. To do this Ryan should: a. construct a normal quantile plot of the residuals and see if the result is an approximately upward sloping straight line
b. plot the residuals vs the predicted values of the response variable and check if the result is a random pattern
c. plot the residuals vs the observed values of the response variable and check if it forms and upward sloping line
d. plot the residuals vs each explanatory variable to check if they are approximately random and form no clear pattern
e. construct a normal quantile plot of the residuals and see if the result is an approximately horizontal straight line
f. construct a normal quantile plot of the residuals and see if the result is an approximately downward sloping straight line
plot the residuals vs the observed values of the response variable and check if it forms and upward sloping line ( C )
Step-by-step explanation:
Ryan should plot the residuals vs the observed values of the response variable and check if it forms and upward sloping line ( C )
The exact right action on what Ryan should do is not listed in the options listed below, hence I have just picked the closest on what Ryan should do if he is testing for normality of the residuals after constructing a multiple regression model
Normality of residuals test is performed to ensure that the residuals are properly/evenly distributed
Four of the 7 students got a sticker, so you need to turn that into a percent. To do that, divide 7 by 4, which gives you .57. That means that 57% of students got a sticker.
