1) In linear multiple regression analysis a common rule of thumb is that the number of cases in the training data should be __________

a)as many as you can get b)twice the number of predictors c)larger than the number of predictors plus 2 multiplied by 5 d)ten times the number of predictors.

2)Suppose a dataset has one dependent variable and five predictors ,three numeric and two categorical having 3 and 5 categories respectively. Given this how many independent variables will be needed to run a linear multiple regression analysis on the dataset?

a)5 b)9c)11d)12

3)Since the range of values of independent variables can vary widely ,it is advisable to_______ before applying the linear multiple regression method.

a) randomly sample the dataset

b)normalize the independent variables

c)minimize over fitting

d)apply data smoothing techniques to the data.