. TRUE/FALSE: (Please use one sentence to explain why it is FALSE if you decide that one statement is FALSE)
(a) The regression through origin model is designed to fit count responses only
(b) The Bonferroni method is always the best way of computing joint CI's of the mean responses, i.e., provides the group of CIs with the narrowest ranges which achieves the claimed family confidence coefficient.
(c) When you want to obtain the smallest variance of the "regression coefficient estimate", you might choose to control the response variable values.
(d) We do not have to check the model assumptions when the regression through origin model is used.
A regression through origin model is designed to fit all such models where x = 0 gives a meaningless response through the intercept based linear model. Hence it not all fits the count responses, it does fit other form of data as well
Hence this statement is false
Yes this statement is true, bonferroni method is best way for computing joint confidence intervals of mean responses
Yes this statement is also true, when we want the least error we need to ensure that all the other factors or variables present in the experimental environment do not change or fluctuate to provide the best relation between the variables included in the study
That is not true, for every model it is important to check the
model assumptions, whether it is simple liner regression model or
the regression model through origin. It is important to esure that
the assumptions are valid for the model to be functional and
hence this statement is false too