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Hello I need help with questions 2 until 9 if possible. If you can please show all work and answers clearly. Thanks for all the help have this project that’s due tonight so I need help on thanks.
27 27889.0526471 10.12 1.09 28 SUMMARY OUTPUT 29 30 Regression Statistics 1 Multiple F 0.986442 32 R Square 0.973068 33 Adjus
Include the computation and explanation of the following in your report 1. Write your regression equation ie. demand function
27 27889.0526471 10.12 1.09 28 SUMMARY OUTPUT 29 30 Regression Statistics 1 Multiple F 0.986442 32 R Square 0.973068 33 Adjusted 0.967681 34 Standard I 32.55341 35 Observati 36 37 ANOVA 38 39 Regressio 40 Residual 41 Total 42 43 44 Intercept 401.0069 1068.237 0.375391 0.711321-1827.3 2629.31 -1827.3 2629.31 45 PCP 46 Income 0.010979 0.009904 1.108646 0.280737 -0.00968 0.031638 -0.00968 0.031638 47 ADE 48 PFBG 25 f S F gnificance MS 4 765759.3 191439.8 180.6505 2.15E-15 20 21194.49 1059.725 24 786953.8 coefficientandard Err t Stat P-value Lower 95%Upper 95%ower 95.09 pper 95.0% -88.3314 19.01379 -4.64565 0.000156-127.993 -48.6694 -127.993 -48.6694 278.8516 95.00408 2.935154 0.008185 80.67661 4770267 80.67661 477.0267 68.66415 61.38019 1.11867 0.276538 -59.3727 196.701 -59.3727 196.701
Include the computation and explanation of the following in your report 1. Write your regression equation ie. demand function, enter information into 2. Using your regression output, write your estimated coefficients into the 3. Interpret all the coefficients. (20pts) excel as per instructions attached and compute the regression equation. (4pts) demand function. (5pts) 4. Using the average values for the independent variables and your estimated 5. Define and interpret the standard error of the estimate AND estimate the 6. Define the coefficient of detemination (R-squared). What percentage of 7. Are the coefficient's statistically significant? i.e does each of the independent 8. Calculate the point price, cross price elasticity, point advertising and point 9. As a Business Analyst, use the analysis you have done to advise your demand function, compute the demand for PIZZA in a typical market. (6pts) range within which actual demand for pizza is expected to fall with a 95% confidence level. (10pts) demand variation is explained by this model? (5pts) variable have a significant effect on the dependent variable? Explain using t stats. (8pts) income elasticity of demand for PIZZA. (12pts) Manager on a. Whether a decrease in the price of PIZZA would increase or decrease revenues b. The impact of increasing advertising dollars on total revenues Explain your answer, using your elasticity estimates (and or regression) including how much revenue would be generated (or lost) by a decrease (e.g $1) in price. (20pts)
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Answer #1

2)
y^= 401.0069 - 88.3314 PCP + 0.010979 Income + 278.8516 ADE + 68.66415 PFBG

3)
slope coefficient - when x is increased by 1 unit keeping other variables constant

then y changes by amount of coeffienct
hence
if PCP in increased by 1 unit, y decreases by 88.3314 units . similarly others


6)
R^2 = 0.9731

hence 97.31 % of variation is explaiend by this model

7)
if |t-stats| > critical value
then we reject the null hypothesis

df =20
critical value = =t.inv.2t(0.05,20)
= 2.085


we conclude that variable is significant
here PCP and ADE are significant
Income and PFBG are not


Please post Q4,5,8,9 again

We have to solve one question or 4 sub-parts at one time

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