a. Compute b; and bo (to 1 decimal). b = bo = Complete the estimated regression equation (to 1 decimal). = b. According to this model, what is the change in annual sales ($1000s) for every year of experience (to 1 decimal)? c. Compute the coefficient of determination (to 3 decimals). Note: report r2 between o and 1. What percentage of the variation in annual sales ($1000s) can be explained by the years of experience of the salesperson (to 1 decimal)? d. A new salesperson joins the team with 6 years of experience. What is the estimated annual sales ($1000s) for the new salesperson (to the nearest whole number)?

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XLMiner Analysis ToolPak
A
В
D
G
K
M
N
P
1 Salesperson
Years of Experience Annual Sales ($1000s)
78
SUMMARY OUTPUT
2
3
Anova: Single Factor
Regression Statistics
Multiple R
R Square
Adjusted R Square
Standard Error
3
3
96
4
3
5
88
0.907961759
Anova: Two-Factor With Replication
4
4
107
0.824394555
6
5
6
105
0.802443875
Anova: Two-Factor Without Replication
7
7
116
8.072755139
8
7
10
123
Observations
10
Correlation
9
8
117
Covariance
10
9
10
122
ANOVA
11
10
14
139
df
SS
MS
F
Significance F
Regression
Descriptive Statistics
12
1
2447.544996 2447.544996 37.55667406 0.000280582
13
Residual
8 521.3550043 65.16937553
Total
9
2968.9
Exponential Smoothing
14
15
F-Test Two-Sample for Variances
16
Coefficients Standard Error t Stat
P-value
Lower 95%
Upper 95%
Lower 95% Upper 95%
Intercept
Years of Experience 4.575705731 0.746645624 6.128350028 0.000280582 2.853937836 6.297473627 2.853937836 6.297473627
17
76.61248931 5.883832818 13.02084741 1.14813E-06 63.04434651 90.18063211 63.04434651 90.18063211
Fourier Analysis
18
19
Histogram
20
21
Linear Regression
22
23
24
Input Y Range: $C$1:SCS11
25
Input X Range: $B$1:$B$11
26
27
V Labels
28
Constant is Zero
29
30
V Confidence Level: 95 %
31
32
Output Range: SJS33
33
O Residuals
34
35
O Residual Plots
36
Standardized Residuals
37
O Line Fit Plots
38
O Normal Probability Plots
39
40
ок
O 0000
Transcribed Image Text:XLMiner Analysis ToolPak A В D G K M N P 1 Salesperson Years of Experience Annual Sales ($1000s) 78 SUMMARY OUTPUT 2 3 Anova: Single Factor Regression Statistics Multiple R R Square Adjusted R Square Standard Error 3 3 96 4 3 5 88 0.907961759 Anova: Two-Factor With Replication 4 4 107 0.824394555 6 5 6 105 0.802443875 Anova: Two-Factor Without Replication 7 7 116 8.072755139 8 7 10 123 Observations 10 Correlation 9 8 117 Covariance 10 9 10 122 ANOVA 11 10 14 139 df SS MS F Significance F Regression Descriptive Statistics 12 1 2447.544996 2447.544996 37.55667406 0.000280582 13 Residual 8 521.3550043 65.16937553 Total 9 2968.9 Exponential Smoothing 14 15 F-Test Two-Sample for Variances 16 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95% Upper 95% Intercept Years of Experience 4.575705731 0.746645624 6.128350028 0.000280582 2.853937836 6.297473627 2.853937836 6.297473627 17 76.61248931 5.883832818 13.02084741 1.14813E-06 63.04434651 90.18063211 63.04434651 90.18063211 Fourier Analysis 18 19 Histogram 20 21 Linear Regression 22 23 24 Input Y Range: $C$1:SCS11 25 Input X Range: $B$1:$B$11 26 27 V Labels 28 Constant is Zero 29 30 V Confidence Level: 95 % 31 32 Output Range: SJS33 33 O Residuals 34 35 O Residual Plots 36 Standardized Residuals 37 O Line Fit Plots 38 O Normal Probability Plots 39 40 ок O 0000
Video
A sales manager collected data on annual sales for new customer accounts and the number of years of experience for a sample of 10 salespersons. In the Microsoft Excel Online file below you will find a
sample of data on years of experience of the salesperson and annual sales. Conduct a regression analysis to explore the relationship between these two variables and then answer the following questions.
Open spreadsheet
a. Compute b; and bo (to 1 decimal).
b =
bo =
Complete the estimated regression equation (to 1 decimal).
b. According to this model, what is the change in annual sales ($1000s) for every year of experience (to 1 decimal)?
c. Compute the coefficient of determination (to 3 decimals). Note: report r2 between 0 and 1.
12 =
What percentage of the variation in annual sales ($1000s) can be explained by the years of experience of the salesperson (to 1 decimal)?
%
d. A new salesperson joins the team with 6 years of experience. What is the estimated annual sales ($1000s) for the new salesperson (to the nearest whole number)?
$
Transcribed Image Text:Video A sales manager collected data on annual sales for new customer accounts and the number of years of experience for a sample of 10 salespersons. In the Microsoft Excel Online file below you will find a sample of data on years of experience of the salesperson and annual sales. Conduct a regression analysis to explore the relationship between these two variables and then answer the following questions. Open spreadsheet a. Compute b; and bo (to 1 decimal). b = bo = Complete the estimated regression equation (to 1 decimal). b. According to this model, what is the change in annual sales ($1000s) for every year of experience (to 1 decimal)? c. Compute the coefficient of determination (to 3 decimals). Note: report r2 between 0 and 1. 12 = What percentage of the variation in annual sales ($1000s) can be explained by the years of experience of the salesperson (to 1 decimal)? % d. A new salesperson joins the team with 6 years of experience. What is the estimated annual sales ($1000s) for the new salesperson (to the nearest whole number)? $
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