Question
In: Statistics and Probability
1. Here are the data from a small bookstore: Number of Salespeople Working Sales (in $1000s)...
1. Here are the data from a small bookstore:
|
Number of Salespeople Working |
Sales (in $1000s) |
|
2 |
10 |
|
3 |
11 |
|
7 |
13 |
|
9 |
14 |
|
10 |
18 |
|
10 |
20 |
|
12 |
20 |
|
15 |
22 |
|
16 |
22 |
|
20 |
26 |
a. Compute the correlation coefficient between number of salespeople and sales. Interpret the correlation coefficient. 6
b. Assuming the conditions for regression are met, find the estimated least-squares regression line and predicted sales on a day with 12 employees working. 7
c. If you expect the population regression coefficient to be positive, perform the hypothesis test of the regression coefficient at significance level of 0.05. 8
d. Find 95% prediction interval for Sales on a day with 12 employees working. 7
e. Comment on the overall quality of the fitted model using appropriate index. 7
Solutions
Expert Solution
a. Compute the correlation coefficient between number of salespeople and sales. Interpret the correlation coefficient
Sol:
the correlation coefficient between number of salespeople and sales is 0.9653.
b. Assuming the conditions for regression are met, find the estimated least-squares regression line and predicted sales on a day with 12 employees working
Sol:
The regression equaion is Y=8.1005+0.9134X
The predicted sales on a day with number of sales people
working
Y=8.10+0.913(12)
=18.9
orchestra answered 2 years agoRelated Solutions
pls answer ASAP. THANKS Q1. Here are the data from a small bookstore: Number of Salespeople...
pls answer ASAP. THANKS
Q1. Here are the data from a small bookstore:
Number of Salespeople
Working
Sales (in $1000s)
2 10
3 11
7 13
9 14
10 18
10 20
12 20
15 22
16 22
20 26
a. Compute the correlation coefficient between number of
salespeople and sales.
Interpret the correlation coefficient.
b. Assuming the conditions for regression are met,
find the estimated least-squares
regression line and predicted sales on a day with 12 employees
working.
c....
The accompanying data show the number of people working and the sales for a small bookstore....
The accompanying data show the number of people working and the
sales for a small bookstore. The regression line is given below.
The bookstore decides to have a gala event in an attempt to drum up
business. They hire 103 employees for the day and bring in a total
of $ 41,000.
Sales = 7.873 + 0.946(Number of Salespeople Working)
Number of Salespeople Working // Sales
2 // 9
3 // 12
7 // 14
9 // 14
10 //...
Consider the following data from a small bookstore: Salespeople Sales ($1000) 2 10 3 11 7...
Consider the following data from a small bookstore:
Salespeople
Sales ($1000)
2
10
3
11
7
13
9
14
10
18
10
20
12
20
15
22
16
22
20
26
Sample mean = 10.4
sample mean = 17.6
SD(x) = 5.64
SD(y) = 5.34
Prepare a scatterplot of Sales against Number of Sales People
Working
What can you say about the direction of the association?
What can you say about the form of the relationship?
What can you say...
Sales data were collected from a small bookstore. The following is an equation for the regression...
Sales data were collected from a small bookstore. The following
is an equation for the regression line of the data.
Sales = 9.12 + 0.818(Number of Salespeople Working)
The assumptions and conditions for regression are met, and
from technology, it is known that SE(b1) = 0.0920 and
Se =1.640.
Number of Salespeople Working // Sales (in $1000s)
1 // 11
2 // 10
6 // 12
9 // 16
9 // 18
10 // 20
13 // 19
14 //...
Data from a small bookstore are shown in the accompanying table. The manager wants to predict...
Data from a small bookstore are shown in the accompanying table.
The manager wants to predict Sales from Number of Sales People
Working. Complete parts a through h below.
Number of ales peaople working
sale (in $1000)
2
10
3
12
5
14
8
15
10
19
10
21
13
21
14
22
17
22
19
27
x(bar)= 10.1
y(bar)=18.3
SD(x)=5.74
SD(y)=5.33
A) find the slope etimate, b1. B) What does
b1 mean, in thi context? C) Find the intercept,...
Refer to the gasoline sales time series data in the given table. Week Sales (1000s of...
Refer to the gasoline sales time series data in the given
table.
Week
Sales (1000s of gallons)
1
18
2
22
3
18
4
24
5
19
6
16
7
21
8
19
9
22
10
19
11
16
12
23
Compute four-week and five-week moving averages for the time
series. Round your answers to two decimal places.
Week
Sales
4-Week
Moving Average
5-Week
Moving Average
1
18
2
22
3
18
4
24
5
19
6
16
7
21...
Refer to the gasoline sales time series data in the given table. Week Sales (1000s of...
Refer to the gasoline sales time series data in the given
table.
Week
Sales (1000s of gallons)
1
17
2
20
3
18
4
22
5
17
6
16
7
22
8
17
9
23
10
21
11
14
12
22
Compute four-week and five-week moving averages for the time
series. Round your answers to two decimal places.
Week
Sales
4-Week
Moving Average
5-Week
Moving Average
1
17
2
20
3
18
4
22
5
17
6
16
7
22...
Refer to the gasoline sales time series data in the given table. Week Sales (1000s of...
Refer to the gasoline sales time series data in the given
table.
Week
Sales (1000s of gallons)
1
17
2
20
3
18
4
22
5
19
6
15
7
21
8
19
9
21
10
19
11
15
12
23
Compute four-week and five-week moving averages for the time
series. If required, round your answers to two decimal
places.
Week
Sales
4 Period
Moving Average
5 Period
Moving Average
1
17
2
20
3
18
4
22
5
19...
Refer to the gasoline sales time series data in the given table. Week Sales (1000s of...
Refer to the gasoline sales time series data in the given
table.
Week
Sales (1000s of gallons)
1
17
2
22
3
19
4
23
5
19
6
16
7
21
8
18
9
22
10
21
11
14
12
22
Compute four-week and five-week moving averages for the time
series. Round your answers to two decimal places.
Week
Sales
4-Week
Moving Average
5-Week
Moving Average
1
17
2
22
3
19
4
23
5
19
6
16
7
21...
Regression analysis was applied between sales data (y in $1000s) and advertising data (x in $100s)...
Regression analysis was applied between sales data (y in $1000s)
and advertising data (x in $100s) and the following information was
obtained. = 30 + 2x n = 17 SSR = 450 SSE = 150
The critical t value for testing the significance of the slope,
at a .05 level of significance, is: 1.746. 2.131. 1.753. 2.120.
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