Question

The general manager of a chain of pharmaceutical stores reported the results of a regression analysis, designed to predict the annual sales for all the stores in the chain (Y) – measured in millions of dollars. One independent variable used to predict annual sales of stores is the size of the store (X) – measured in thousands of square feet. Data for 14 pharmaceutical stores were used to fit a linear model. The results of the simple linear regression are provided below.

        Y = 0.964 + 1.670X; S_YX =$0.9664 million; 2 – tailed p value = 0.00004 (for testing ß₁);                          

                        S_b1=0.157;    X = 2.9124; SSX=Σ( X_i –X )²=37.924;   n=14 ;

        Which is the correct statement?

    

		All the annual sales will increase by at least 0.964 million dollars.
		The annual sales increase by 0.964 million dollars, we expect the size of the pharmaceutical store to increase by 1.0 thousand sq. feet.
		We estimate an average change of 1.670 million dollars in annual sales for each 1.0 thousand sq. foot increase in the size of the pharmaceutical store.
		For every increase of 1.0 thousand sq. feet in the size of the pharmaceutical store we         expect annual sales to increase by 0.9664 millions of dollars.

Answer 1

The correct statement among given ones is:

We estimate an average change of 1.670 million dollars in annual sales for each 1.0 thousand sq. foot increase in the size of the pharmaceutical store.

Option C is correct.