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The following data represent the number of flash drives sold per day at a local computer shop and their prices. Price Units Sold 34 3 36 4 32 6 35 5 30 9 38 2 40 1 a. Develop the estimated regression equation that could be used to predict the quantity sold given the price. Interpret the slope. b. Did the estimated regression equation provide a good fit? Explain. c. Compute the sample correlation coefficient between the price and the number of flash drives sold. Use a= 0.01 to test the relationship between price and units sold.

The following data represent the number of flash drives sold per day at a local computer shop and their prices. Price Units Sold 34 3 36 4 32 6 35 5 30 9 38 2 40 1 a. Develop the estimated regression equation that could be used to predict the quantity sold given the price. Interpret the slope. b. Did the estimated regression equation provide a good fit? Explain. c. Compute the sample correlation coefficient between the price and the number of flash drives sold. Use a= 0.01 to test the relationship between price and units sold.

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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The following data represent the number of flash drives sold per day at a local
computer shop and their prices.
Price Units Sold
34 3
36 4
32 6
35 5
30 9
38 2
40 1
a. Develop the estimated regression equation that could be used to predict the
quantity sold given the price. Interpret the slope.

b. Did the estimated regression equation provide a good fit? Explain.

c. Compute the sample correlation coefficient between the price and the number of
flash drives sold. Use a= 0.01 to test the relationship between price and units sold.

d. How many units can be sold per day if the price of flash drive is set to $28.

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