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TABLE 1



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 stores were used to fit a linear model.

The results of the simple linear regression are provided below.



^

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

Sb1=0.157; X = 2.9124; SSX=Σ( Xi –X )2=37.924; n=14 ;

Referring to Table 1, the general manager wanted to test the null hypothesis that the true slope of size of store and annul sales was equal to one. The value of the test statistic is:



0.1570

0.4268

4.2675


1.6700

  • stats -

    0.4168

  • stats -

    .4268

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