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) 9
c) 11
d) 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.