Question

Carlson Mining, Inc. has 12 large pumps that pump water from the mines it operates.
Management has been concerned lately about the amount of money required to
repair malfunctioning pumps. These costs are sums over and above the amounts
spent for routine maintenance. When asked what factors they thought might affect
the mean monthly repair costs, employees suggested the age of the pumps and the
number of hours of operation. The following information was collected.
Choose the relevant Summary Output to answer the questions. Note that the
mean monthly repair costs are in dollars, so when questions ask about repair
costs, make sure that your answers reflect that.
Mean Weekly Hours of Operation over Past Year	Age of Pump at First of Year (months)	Mean Monthly Repair Costs over Past Year
28	80	$1,049
26	48	$1,095
15	27	$882
12	2	$447
16	13	$715
21	55	$542
13	30	$415
21	35	$454
16	36	$495
12	13	$370
18	28	$448
18	49	$509

According to your equation, holding the age of the pumps constant, for each hour
increase in the mean weekly hours of operation, the mean monthly repair costs
(increase / do not change / decrease) by ____ ROUND APPROPRIATELY
AND INCLUDE THE UNITS!
How much of the variability in mean monthly repair costs is explained by the
estimated regression equation?

Answer 1

Below is given the SPSS output for regression. we will answer the given questions unig that output only

From the above table we can see that the regression equation is

Mean Monthly Repair Costs over Past Year= -87.700 + 45.097* (Mean Weekly Hours of Operation over Past Year )-3.047* (Age of Pump at First of Year)

from this equation we can see that

One hour increase holding the age of the pumps constant, for each hour ncrease in the mean weekly hours of operation, the mean monthly repair costs increases by $45. (rounded)

R square is the value which tells us the percentage variation in dependent variable is explained by the independent variables used in regression. From the above table we can see that R square= 0.510.

Hence the variability in mean monthly repair costs is explained by the estimated regression equation is 51%.