*Q6) provide all relevant computer output Run a regression analysis on the data
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Question
*Q6)
provide all relevant computer output
Run a regression analysis on the data below in Excel. The file shows how 64 customers of Xerox Copiers replied to 4 questions (see the labels in the file for each question; 1=very dissatisfied and 10=very satisfied). Investigate how the three departmental satisfaction attributes influence overall satisfaction. For each of the tasks below, provide the hypothesis tested, the empirical F-value with degrees of freedom, the critical F-value
PLEASE ANSWER THE QUESTIONS BELOW:
(hint: if the exact df that you need is not in the table, use the next closest number), the p-value, the decision rule, whether you accept or reject the chosen Ho at a confidence level of 95%, the percent of variation in overall satisfaction explained, and a verbal interpretation of the outcome.
Also, as a manager with Xerox after looking at the result, what should you focus on if your goal is to increase overall satisfaction, and can you somewhat ignore one of the three departments?
1) Run a regression with service as the only predictor for overall satisfaction
2) Run a regression with accounting as the only predictor for overall satisfaction
3) Run a regression with sales as the only predictor for overall satisfaction
4) Run a regression with all three (service, product, sales) as the predictors for overall satisfaction
respondent# Sat with Service dept Sat with Accounting dept Sat with Sales dept Overall Satisfaction 1028 6 6 6 6 1029 8 5 8 10 1030 3 6 3 4 1031 3 3 3 3 1032 9 8 8 10 1033 1 1 1 1 1034 8 8 8 6 1035 6 6 6 6 1036 2 2 2 6 1037 6 7 7 6 1038 3 7 3 6 1039 3 3 3 6 1040 3 7 6 2 1041 8 5 6 8 1043 5 5 5 4 1044 3 3 3 3 1045 2 2 2 2 1046 6 6 6 8 1047 1 3 3 3 1048 1 5 5 7 1049 8 8 7 8 1050 2 3 3 3 1051 1 1 1 1 1052 2 8 5 7 1053 10 6 7 10 1055 9 8 8 8 1056 8 5 5 8 1057 8 8 8 2 1058 6 6 6 6 1059 1 5 5 6 1060 8 8 8 8 1061 4 4 1 3 1062 5 7 7 7 1063 6 2 2 6 1064 2 7 8 7 1065 8 6 6 6 1066 4 9 9 7 1067 8 10 10 10 1069 1 1 1 4 1071 1 1 1 1 1073 2 2 2 3 1074 5 6 6 6 1075 4 4 3 1 1076 5 5 5 2 1077 1 1 1 6 1078 3 7 7 4 1079 4 2 1 5 1080 6 4 8 7 1082 7 2 4 7 1083 1 1 1 1 1084 4 9 9 7 1085 1 2 2 4 1087 4 3 3 8 1088 3 3 3 3 1089 2 2 2 4 1090 5 7 7 6 1091 2 2 2 4 1092 2 10 3 4 1093 4 8 8 5 1094 1 1 1 1 1095 1 9 9 9 1096 6 7 8 5 1097 7 4 9 7 1098 7 4 4 6Explanation / Answer
Answer:
Regression Analysis
r²
0.362
n
64
r
0.602
k
1
Std. Error
2.008
Dep. Var.
Overall Satisfaction
ANOVA table
Source
SS
df
MS
F
p-value
Regression
141.8421
1
141.8421
35.19
1.45E-07
Residual
249.9079
62
4.0308
Total
391.7500
63
Regression output
confidence interval
variables
coefficients
std. error
t (df=62)
p-value
95% lower
95% upper
Intercept
2.8633
0.4832
5.926
1.48E-07
1.8974
3.8291
Sat with Service dept
0.5679
0.0957
5.932
1.45E-07
0.3766
0.7593
The regression line is Overall Satisfaction =2.8633+0.5679* Sat with Service dept
Calculated F=35.19 > critical value F(1,62) =4. Ho is rejected. P=0.0000
For one unit increase in Sat with Service dept, there is an increase of 0.5679 in overall satisfaction.
2) Run a regression with accounting as the only predictor for overall satisfaction
Regression Analysis
r²
0.279
n
64
r
0.528
k
1
Std. Error
2.134
Dep. Var.
Overall Satisfaction
ANOVA table
Source
SS
df
MS
F
p-value
Regression
109.3128
1
109.3128
24.00
7.25E-06
Residual
282.4372
62
4.5554
Total
391.7500
63
Regression output
confidence interval
variables
coefficients
std. error
t (df=62)
p-value
95% lower
95% upper
Intercept
2.8395
0.5710
4.973
5.52E-06
1.6981
3.9809
Sat with Accounting dept
0.5009
0.1022
4.899
7.25E-06
0.2965
0.7052
The regression line is Overall Satisfaction =2.8395+0.5009* Sat with Accounting dept
Calculated F=24.00 > critical value F(1,62) =4. Ho is rejected. P=0.0000
For one unit increase in Sat with Accounting dept, there is an increase of 0.5009 in overall satisfaction.
Regression Analysis
r²
0.424
n
64
r
0.651
k
1
Std. Error
1.908
Dep. Var.
Overall Satisfaction
ANOVA table
Source
SS
df
MS
F
p-value
Regression
166.0727
1
166.0727
45.62
5.71E-09
Residual
225.6773
62
3.6400
Total
391.7500
63
Regression output
confidence interval
variables
coefficients
std. error
t (df=62)
p-value
95% lower
95% upper
Intercept
2.4098
0.4915
4.903
7.13E-06
1.4273
3.3922
Sat with Sales dept
0.5993
0.0887
6.755
5.71E-09
0.4219
0.7766
The regression line is Overall Satisfaction =2.4098+0.5993* Sat with Sales dept
Calculated F=45.62 > critical value F(1,62) =4. Ho is rejected. P=0.0000
For one unit increase in Sat with Sales dept, there is an increase of 0.5993 in overall satisfaction.
4) Run a regression with all three (service, product, sales) as the predictors for overall satisfaction
Regression Analysis
R²
0.484
Adjusted R²
0.458
n
64
R
0.695
k
3
Std. Error
1.836
Dep. Var.
Overall Satisfaction
ANOVA table
Source
SS
df
MS
F
p-value
Regression
189.4143
3
63.1381
18.72
1.09E-08
Residual
202.3357
60
3.3723
Total
391.7500
63
Regression output
confidence interval
variables
coefficients
std. error
t (df=60)
p-value
95% lower
95% upper
Intercept
2.0059
0.5280
3.799
.0003
0.9496
3.0621
Sat with Service dept
0.2988
0.1140
2.621
.0111
0.0708
0.5269
Sat with Accounting dept
0.0104
0.1585
0.066
.9478
-0.3067
0.3275
Sat with Sales dept
0.4060
0.1749
2.322
.0237
0.0562
0.7558
The regression line is Overall Satisfaction =2.0059+0.2988* Sat with Service dept+0.0104* Sat with Accounting dept+0.4060* Sat with Sales dept
Calculated F=18.72 > critical value F(3,62) = 2.753. Ho is rejected. P=0.0000
Sat with Sales dept and Sat with Service dept are significantly contributing to Overall Satisfaction.
Regression Analysis
r²
0.362
n
64
r
0.602
k
1
Std. Error
2.008
Dep. Var.
Overall Satisfaction
ANOVA table
Source
SS
df
MS
F
p-value
Regression
141.8421
1
141.8421
35.19
1.45E-07
Residual
249.9079
62
4.0308
Total
391.7500
63
Regression output
confidence interval
variables
coefficients
std. error
t (df=62)
p-value
95% lower
95% upper
Intercept
2.8633
0.4832
5.926
1.48E-07
1.8974
3.8291
Sat with Service dept
0.5679
0.0957
5.932
1.45E-07
0.3766
0.7593
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