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bachelor in business administration
Polytechnic State University Sanluis
Jan-2006 - Nov-2010
CPA
Polytechnic State University
Jan-2012 - Nov-2016
Professor
Harvard Square Academy (HS2)
Mar-2012 - Present
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14.6Â Â Â Â Â Â THE FRESH DETERGENT CASE
DSÂ Fresh
Enterprise Industries produces Fresh, a brand of liquid laundry detergent. In order to study the relationship between price and demand for the large bottle of Fresh, the company has gathered data concerning demand for Fresh over the last 30 sales periods (each sales period is four weeks). Here, for each sales period,
y = demand for the large bottle of Fresh (in hundreds of thousands of bottles) in the sales period, and
x = the difference between the average industry price (in dollars) of competitors’ similar detergents and the price (in dollars) of Fresh as offered by Enterprise Industries in the sales period.
The data and MINITAB output from fitting a least squares regression line to the data follow below.
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Sales Period |
 y |
 x |
 |
Sales Period                  y                      x |
 |
|
1 |
7.38 |
-.05 |
 |
24Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â 8.50Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â .10 |
||
2 |
8.51 |
.25 |
 |
25Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â 8.75Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â .50 |
||
3 |
9.52 |
.60 |
 |
26Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â 9.21Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â .60 |
||
4 |
7.50 |
0 |
 |
27Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â 8.27Â Â Â Â Â Â Â Â Â Â Â Â Â Â -.05 |
||
5 |
9.33 |
.25 |
 |
28Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â 7.67Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â 0 |
||
6 |
8.28 |
.20 |
 |
29Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â 7.93Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â .05 |
||
7 |
8.75 |
.15 |
 |
30Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â 9.26Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â .55 |
||
8 |
7.87 |
.05 |
 |
 |
||
9 |
7.10 |
-.15 |
 |
 |
||
10 |
8.00 |
.15 |
 |
 |
||
11 |
7.89 |
.20 |
 |
Fitted Line Plot |
 |
 |
12 |
8.15 |
.10 |
 |
Demand = 7.814 + 2.665 PriceDif |
 |
 |
13 14 |
9.10 8.86 |
.40 .45 |
 |
9.5 |
 |
 |
15 |
8.90 |
.35 |
 |
9.0 |
 |
 |
16 |
8.87 |
.30 |
 |
 |
 |
 |
17 |
9.26 |
.50 |
 |
8.5 |
 |
 |
18 |
9.00 |
.50 |
 |
8.0 |
 |
 |
19 |
8.75 |
.40 |
 |
 |
 |
 |
20 |
7.95 |
-.05 |
 |
7.5 |
 |
 |
21 |
7.65 |
-.05 |
 |
7.0 |
 |
 |
22 |
7.27 |
-.10 |
 |
-0.2Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â 0.0Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â 0.2Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â 0.4 |
0.6 |
 |
23 |
8.00 |
.20 |
 |
PriceDif |
 |
 |
 |
 |
 |
 |
 |
 |
 |
DSÂ Fresh |
 |
 |
 |
 |
 |
 |
a    Find the least squares point estimates b0 and b1 on the computer output and report their values.
b    Interpret b0 and b1. Does the interpretation of b0 make practical sense?
c    Write the equation of the least squares line.
d   Use the least squares line to compute a point estimate of the mean demand in all sales periods when the price difference is .10 and a point prediction of the actual demand in an individual sales period when the price difference is .10.
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