A drycleaning chain is assessing the relationship between Ho

A dry-cleaning chain is assessing the relationship between \"Hours of operation (X)\", & \"Sales Revenue (Y)\" During 1 month in 2012, data was collected from n-39 stores. Use computer output for questions 20 and 21. Coefficients Standard Error tStat P-value Intercept 1576.21341.17 11341.17 4.621 0.000 4.62 0.0001 Hours ( 196.75 1.50 0.1479 145.13 20. In the computer output above, the slope coefficient indicates that for every one unit increase in a) Sales Revenue(Y), there is a $1576.21 increase in Hours of Operation b) Sales Revenue(Y), there is a 96.75 percent increase in Hours of Operation c) Hours of Operation(X), there is a $145.13 increase in Sales Revenue d) Hours of Operation(X), there is a 14.79 percent increase in Sales Revenue

Solution

20.

C is the answer. With unit increase in hours of operation there is $145.13 increase in sales revenue

$145.13 is the slope of the line of regression.

21.

0.1479 is very high > 10% we fail to reject null hypothesis slope is zero

Hence B is the answer

Hours is not statistically significant predictor , drop it from line of regression

22.

Answer is B

As the problems completed increases the time completed increases and time remaining

Decreases.

23.

Answer is B

With increase in X the value of Y decreases.

20. C is the answer. With unit increase in hours of operation there is $145.13 increase in sales revenue $145.13 is the slope of the line of regression. 21. 0.1479 is very high > 10% we fail to reject null hypothesis slope is zero Hence B is the answer Hours is not statistically significant predictor , drop it from line of regression 22. Answer is B As the problems completed increases the time completed increases and time remaining Decreases. 23. Answer is B With increase in X the value of Y decreases.