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ID: 3364387 • Letter: M
Question
MindTap, Cengage Learning × C | ng cengage.com/st. ng.cengage.com/activityservice,·.. E3 Government & Militar.. 80% … | asearch NMAC Finance Accou. @ Firstmark Services e Sean Johnson ? Excel Online template 12.3 Microsoft Excel: Free-form Activity Due on Dec 3 pt 11:59 PM CST FILE HOME INSERT DATA REVIEW VEW Tell me what Question Excel Freeform Activity: Linear Regression and the Coefficient of Determination 1 Salesperson Years of Experience Annual Sales ($1000s) A sales manager collected data on annual sales for new customer accounts and the number of years of exp for a sample of 10 salespersons. In the Microsoft Excel Online file below you experience of the salesperson and annual sales. Conduct a these two variables and then answer the following questians. erience will find a sample of iata on years of hip between regression analysis to explare the 92 94 105 106 109 123 119 119 140 6 a. Compute Di and bo (to 1 decimal) 10 10 10 12 14 16 18 10 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) 7 c. Compute the coefficient of determination (to 3 decimals). Note: report r2 between 0 and 1 19 What percentage of the variation in annual sales ($10005) can be expiained by the years of experience of the salesperson (to 1 decimal)? 23 24 25 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)? 27 28Explanation / Answer
Result:
a).
b1=4.5, bo=75.2
regression equation , y=75.2+4.5*x
b). 4.5
c). 0.954
percentage: 95.4%
estimated annual income when x=6 is 102 ( in $1000s).
Regression Analysis
r²
0.954
n
10
r
0.976
k
1
Std. Error
3.986
Dep. Var.
sales
ANOVA table
Source
SS
df
MS
F
p-value
Regression
2,608.9828
1
2,608.9828
164.19
1.30E-06
Residual
127.1172
8
15.8897
Total
2,736.1000
9
Regression output
confidence interval
variables
coefficients
std. error
t (df=8)
p-value
95% lower
95% upper
Intercept
75.1655
2.9048
25.876
5.34E-09
68.4670
81.8640
year
4.4713
0.3489
12.814
1.30E-06
3.6666
5.2759
Predicted values for: sales
95% Confidence Interval
95% Prediction Interval
year
Predicted
lower
upper
lower
upper
Leverage
6
101.993
98.846
105.141
92.277
111.709
0.117
Regression Analysis
r²
0.954
n
10
r
0.976
k
1
Std. Error
3.986
Dep. Var.
sales
ANOVA table
Source
SS
df
MS
F
p-value
Regression
2,608.9828
1
2,608.9828
164.19
1.30E-06
Residual
127.1172
8
15.8897
Total
2,736.1000
9
Regression output
confidence interval
variables
coefficients
std. error
t (df=8)
p-value
95% lower
95% upper
Intercept
75.1655
2.9048
25.876
5.34E-09
68.4670
81.8640
year
4.4713
0.3489
12.814
1.30E-06
3.6666
5.2759
Predicted values for: sales
95% Confidence Interval
95% Prediction Interval
year
Predicted
lower
upper
lower
upper
Leverage
6
101.993
98.846
105.141
92.277
111.709
0.117