1, Estimate a linear regression, with Quantity as your dependent (y) variable. Your independent variables are Price, Xmas, Summer, and the Day of the Week variables. 2. Write out the estimated equation.  3. For each value of price (0 through 100 in increments of 5), plug the price into the estimated regression equation to get a “predicted quantity.” What is the average of these predicted quantities?  Quantity day Price Xmas Summer Monday Tuesday Wednesday Thursday Friday Saturday Sunday 121 1 62 0 0 1 0 0 0 0 0 0 168 2 44 0 0 0 1 0 0 0 0 0 132 3 52 0 0 0 0 1 0 0 0 0 230 4 16 0 0 0 0 0 1 0 0 0 232 5 28 0 0 0 0 0 0 1 0 0 368 6 7 0 0 0 0 0 0 0 1 0 225 7 63 0 0 0 0 0 0 0 0 1 115 8 63 0 0 1 0 0 0 0 0 0 143 9 50 0 0 0 1 0 0 0 0 0 79 10 74 0 0 0 0 1 0 0 0 0 85 11 61 0 0 0 0 0 1 0 0 0 210 12 47 0 0 0 0 0 0 1 0 0 265 13 41 0 0 0 0 0 0 0 1 0 348 14 20 0 0 0 0 0 0 0 0 1 117 15 61 0 0 1 0 0 0 0 0 0 124 16 49 0 0 0 1 0 0 0 0 0 45 17 89 0 0 0 0 1 0 0 0 0

MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
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Chapter1: Starting With Matlab
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1, Estimate a linear regression, with Quantity as your dependent (y) variable. Your independent variables are Price, Xmas, Summer, and the Day of the Week variables.

2. Write out the estimated equation. 

3. For each value of price (0 through 100 in increments of 5), plug the price into the estimated regression equation to get a “predicted quantity.” What is the average of these predicted quantities? 

Quantity day Price Xmas Summer Monday Tuesday Wednesday Thursday Friday Saturday Sunday
121 1 62 0 0 1 0 0 0 0 0 0
168 2 44 0 0 0 1 0 0 0 0 0
132 3 52 0 0 0 0 1 0 0 0 0
230 4 16 0 0 0 0 0 1 0 0 0
232 5 28 0 0 0 0 0 0 1 0 0
368 6 7 0 0 0 0 0 0 0 1 0
225 7 63 0 0 0 0 0 0 0 0 1
115 8 63 0 0 1 0 0 0 0 0 0
143 9 50 0 0 0 1 0 0 0 0 0
79 10 74 0 0 0 0 1 0 0 0 0
85 11 61 0 0 0 0 0 1 0 0 0
210 12 47 0 0 0 0 0 0 1 0 0
265 13 41 0 0 0 0 0 0 0 1 0
348 14 20 0 0 0 0 0 0 0 0 1
117 15 61 0 0 1 0 0 0 0 0 0
124 16 49 0 0 0 1 0 0 0 0 0
45 17 89 0 0 0 0 1 0 0 0 0
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