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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
Compute b1 and b0 (to 1 decimal).
b1 =
b0 =
Complete the estimated regression equation (to 1 decimal).
= + x
According to this model, what is the change in annual sales ($1000s) for every year of experience (to 1 decimal)?
Compute the coefficient of determination (to 3 decimals). Note: report r2 between 0 and 1.
r2 =
What percentage of the variation in annual sales ($1000s) can be explained by the years of experience of the salesperson (to 1 decimal)?
%
A new salesperson joins the team with 8 years of experience. What is the estimated annual sales ($1000s) for the new salesperson (to the nearest whole number)?
1 1 85
2 3 97
3 3 95
4 5 97
5 7 105
6 8 106
7 10 122
8 10 120
9 12 113
10 12 134

Respuesta :

fichoh

Answer:

Kindly check explanation

Step-by-step explanation:

Given :

Years of experience (X) :

1

3

3

5

7

8

10

10

12

12

Annual sales (Y) :

85

97

95

97

105

106

122

120

113

134

The estimated regression equation obtained is :

y = b0 + b1x

b0 = 82.82967

b1 = 3.46061

ŷ = 3.46061X + 82.82967

The change in annual sales for every year of experience is given by the slope value, b1 = 3.46061 = 3.5 (1 decimal place)

The Coefficient of determination R² = 0.8477 = 0.848 ( 3 decimal place).

The Coefficient of determination gives the proportion of explained variance.

About 84.8% percent variation in annual sales can be explained by years of experience of the sales person.

Using the regression equation :

ŷ = 3.46061X + 82.82967

Years of experience, x = 8

ŷ = 3.46061(8) + 82.82967 = 110.514

111 = (to the nearest whole number)

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