SUMMARY OUTPUT Regression Statistics Multiple R R-Square Adjusted R-Square Standard Error Observations 0.38 '2' 20.77 150 Analysis of Varlance Degrees of Freedom Sum of Squares Mean Square Significance F Regression Residual Total 2 147 *3 5199.43 12.05 0.00 63,408.62 73,807.49 431.35 *4 Coefficients Standard Error t-Statistic P-Value Lower 95% Upper 95% Intercept 58.87 '5' 3.84 0.00 28.59 89.15 0.85 .9, 4.64 Price of X -1.64 0.06 -3.31 0.04 Income '7' 0.24 0.00 0.63 1.56
SUMMARY OUTPUT Regression Statistics Multiple R R-Square Adjusted R-Square Standard Error Observations 0.38 '2' 20.77 150 Analysis of Varlance Degrees of Freedom Sum of Squares Mean Square Significance F Regression Residual Total 2 147 *3 5199.43 12.05 0.00 63,408.62 73,807.49 431.35 *4 Coefficients Standard Error t-Statistic P-Value Lower 95% Upper 95% Intercept 58.87 '5' 3.84 0.00 28.59 89.15 0.85 .9, 4.64 Price of X -1.64 0.06 -3.31 0.04 Income '7' 0.24 0.00 0.63 1.56
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
A quant jock from your firm used a linear demand specification to estimate the demand for its product and sent you a hard copy of the results. Unfortunately, some entries are missing because the toner was low in her printer. Use the information presented below to find the missing values labeled ‘1’ through ‘7’ (round your answers to the nearest hundredth). Then, answer the accompanying questions. a. Based on these estimates, write an equation that summarizes the demand for the firm’s product. b. Which regression coefficients are statistically significant at the 5 percent level? c. Comment on how well the regression line fits the data.

Transcribed Image Text:SUMMARY OUTPUT
Regression Statistics
Multiple R
R-Square
Adjusted R-Square
Standard Error
Observations
0.38
'2'
20.77
150
Analysis of Varlance
Degrees of
Freedom
Sum of Squares Mean Square
Significance F
Regression
Residual
Total
2
147
*3
5199.43
12.05
0.00
63,408.62
73,807.49
431.35
*4
Coefficients
Standard Error
t-Statistic
P-Value
Lower 95%
Upper 95%
Intercept
58.87
'5'
3.84
0.00
28.59
89.15
0.85
.9,
4.64
Price of X
-1.64
0.06
-3.31
0.04
Income
'7'
0.24
0.00
0.63
1.56
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