In: Statistics and Probability
Imagine you work for Company Xtreme, and you are interested in seeing how consumer brand loyalty influences how much consumers spend weekly on their products. 25 customers completed a survey in which participants were asked to indicate “To what extent do you agree with the following statement: I consider myself to be brand loyal to Company Xtreme” (1 = Strongly Disagree to 7 = Strongly Agree). Additionally, you asked participants to “please write down how much you spend weekly on Company Xtreme products”. The results of the survey are listed in the table below:
1. Calculate the simple regression equation that predicts average weekly expenditures based on participant's brand loyalty scores. Then, predict the average weekly expenditures of an individual with a brand loyalty score of 4.
Participant (i) | Brand Loyalty | Average Weekly Expenditures |
1 | 3 | $126 |
2 | 6 | $475 |
3 | 5 | $207 |
4 | 6 | $347 |
5 | 4 | $103 |
6 | 4 | $74 |
7 | 2 | $53 |
8 | 1 | $47 |
9 | 5 | $177 |
10 | 2 | $4 |
11 | 2 | $73 |
12 | 6 | $223 |
13 | 4 | $121 |
14 | 7 | $504 |
15 | 4 | $51 |
16 | 1 | $0 |
17 | 2 | $50 |
18 | 7 | $459 |
19 | 5 | $266 |
20 | 6 | $403 |
21 | 1 | $75 |
22 | 6 | $350 |
23 | 4 | $272 |
24 | 7 | $364 |
25 | 5 | $302 |
Solution
we will solve it by using excel and the steps are
Enter the Data into excel
Click on Data tab
Click on Data Analysis
Select Regression
Select input Y Range as Range of dependent variable.
Select Input X Range as Range of independent variable
click on labels if your selecting data with labels
click on ok.
So this is the output of Regression in Excel.
SUMMARY OUTPUT | ||||||||
Regression Statistics | ||||||||
Multiple R | 0.8823 | |||||||
R Square | 0.7785 | |||||||
Adjusted R Square | 0.7689 | |||||||
Standard Error | 76.3106 | |||||||
Observations | 25.0000 | |||||||
ANOVA | ||||||||
df | SS | MS | F | Significance F | ||||
Regression | 1.0000 | 470706.8430 | 470706.8430 | 80.8315 | 0.0000 | |||
Residual | 23.0000 | 133936.1170 | 5823.3094 | |||||
Total | 24.0000 | 604642.9600 | ||||||
Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% | |
Intercept | -92.1681 | 36.4106 | -2.5314 | 0.0187 | -167.4892 | -16.8470 | -167.4892 | -16.8470 |
Brand Loyalty | 70.7638 | 7.8708 | 8.9906 | 0.0000 | 54.4818 | 87.0459 | 54.4818 | 87.0459 |
Using above output the regression equation
Average Weekly Expenditures = -92.1681+70.7638*Brand Loyalty
predict the average weekly expenditures of an individual with a brand loyalty score of 4.
Average Weekly Expenditures = -92.1681+70.7638*Brand Loyalty
Average Weekly Expenditures = -92.1681+70.7638*4
Average Weekly Expenditures = $190.8871