Question 2If price is $5 and income is $15, what is price elasticity? (Round your answer to two decimal places. If you answer is a number between -1 and 1, please do not omit the zero in the front. For example, you should have your answer as -0.46 instead of -.46). Which of the following coefficients are statistically significant at the 5%level? Select all that apply.InterceptIncomePrice An analyst from your firm used a linear demand specification to estimatethe demand for its productand sent you a hard copy of the results:SUMMARY OUTPUTRegression StatisticsMultiple RR SquareAdjusted R SquareStandard ErrorObservationsANOVARegressionResidualTotalInterceptIncomePrice0.067350.00454-0.0022444.03878297df2.00294.00296.00SS78.260.75-1.862597.84570187.72572785.56Coefficients Standard Error7.001.471.77MS1298.921939.41t Stat11.180.51-1.05F0.67P-value0.000.610.29Significance F0.51Lower 95%64.49-2.15-5.33Upper 95%92.043.651.62Lower 95.0% Upper 95.0%64.4992.04-2.153.65-5.331.62

From the above table:- Intercept = 78.26 Coefficient of Income= 0.75 and coefficient of price =…

Answered: Which of the following coefficients are…

Which of the following coefficients are statistically significant at the 5% level? Select all that apply. Intercept Income Price

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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Question

Question 2

If price is $5 and income is $15, what is price elasticity? (Round your answer to two decimal places. If you answer is a number between -1 and 1, please do not omit the zero in the front. For example, you should have your answer as -0.46 instead of -.46).

Which of the following coefficients are statistically significant at the 5%
level? Select all that apply.
Intercept
Income
Price

An analyst from your firm used a linear demand specification to estimate
the demand for its product
and sent you a hard copy of the results:
SUMMARY OUTPUT
Regression Statistics
Multiple R
R Square
Adjusted R Square
Standard Error
Observations
ANOVA
Regression
Residual
Total
Intercept
Income
Price
0.06735
0.00454
-0.00224
44.03878
297
df
2.00
294.00
296.00
SS
78.26
0.75
-1.86
2597.84
570187.72
572785.56
Coefficients Standard Error
7.00
1.47
1.77
MS
1298.92
1939.41
t Stat
11.18
0.51
-1.05
F
0.67
P-value
0.00
0.61
0.29
Significance F
0.51
Lower 95%
64.49
-2.15
-5.33
Upper 95%
92.04
3.65
1.62
Lower 95.0% Upper 95.0%
64.49
92.04
-2.15
3.65
-5.33
1.62

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