Bookstore sales revisited Recall the data we saw in Chapter 6, Exercise 3 for a bookstore. The manager wants to predict Sales from Number of Sales People Working. Number of Sales People Working Sales (in $1000) 2 10 3 11 7 13 9 14 10 18 10 20 12 20 15 22 16 22 20 26 Dependent variable is Sales R-squared = 93.2, s = 1.477 Variable Coefficient Intercept 8.1006 Num_Workers 0.9134 Here is the regression analysis of Sales vs. Number of Sales People Working. a) Write the regression equation. Define the variables used in your equation. b) What does the slope mean in this context? c) What does the y-intercept mean in this context? Is it meaningful? d) If 18 people are working, what Sales do you predict? e) If sales for the 18 people are actually $25,000, what is the value of the residual? f) Have we overestimated or underestimated the sales?
Bookstore sales revisited Recall the data we saw in Chapter 6, Exercise 3 for a bookstore. The manager wants to predict Sales from Number of Sales People Working. Number of Sales People Working Sales (in $1000) 2 10 3 11 7 13 9 14 10 18 10 20 12 20 15 22 16 22 20 26 Dependent variable is Sales R-squared = 93.2, s = 1.477 Variable Coefficient Intercept 8.1006 Num_Workers 0.9134 Here is the regression analysis of Sales vs. Number of Sales People Working. a) Write the regression equation. Define the variables used in your equation. b) What does the slope mean in this context? c) What does the y-intercept mean in this context? Is it meaningful? d) If 18 people are working, what Sales do you predict? e) If sales for the 18 people are actually $25,000, what is the value of the residual? f) Have we overestimated or underestimated the sales?
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question
Bookstore sales revisited Recall the data we saw in
Chapter 6, Exercise 3 for a bookstore. The manager wants
to predict Sales from Number of Sales People Working.
Number of Sales
People Working Sales (in $1000)
2 10
3 11
7 13
9 14
10 18
10 20
12 20
15 22
16 22
20 26
Dependent variable is Sales
R-squared = 93.2,
s = 1.477
Variable Coefficient
Intercept 8.1006
Num_Workers 0.9134
Here is the
Sales People Working.
a) Write the regression equation. Define the variables
used in your equation.
b) What does the slope mean in this context?
c) What does the y-intercept mean in this context? Is it
meaningful?
d) If 18 people are working, what Sales do you predict?
e) If sales for the 18 people are actually $25,000, what is
the value of the residual?
f) Have we overestimated or underestimated the sales?
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