You are partner at Ernst and Young, and an analyst shows you the following regressionoutput, done in Excel, of a stock's return on the difference between the market return and therisk free return. This is the screenshot. What is the alpha of the stock?SUMMARY OUTPUTRegression StatisticsMultiple RR SquareAdjusted R SquaStandard ErrorObservationsANOVARegressionResidualTotalInterceptX Variable 11.0060.990.00050.020.9919929870.9840500870.9836610640.004580191df4314142Coefficients0.0005159561.006161901SSMSF Significance F0.053065211 0.053065211 2529.547 1.78967E-380.000860104 2.09781E-050.053925315Standard Errort StatP-value Lower 95%Upper 95% Lower 95.0%0.000712079 0.724577382 0.472826 -0.000922117 0.001954029 -0.0009221170.020005366 50.29460082 1.79E-38 0.965760245 1.046563558 0.965760245Upper 95.0%0.0019540291.046563558

The regression model shows the relationship between 1 dependent variable and 1 or more independent…

Answered: You are partner at Ernst and Young, and…

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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You run a Regression analysis using the Data Analysis Toolpak in Excel. The table below shows part of the output. Given these values, what is the equation of the regression line (trend line)?
Identify the correct statement concerning, r the correlation coefficie between X and Y and the linear regression, Y = aX+b. A. Both can be used to show cause and effect. B. Both quantify the strength of relationship between X and Y. C. X and Y are interchangeable in both relationships. D. Both can be used to make predictions.
Use the pizza cost and the subway fare in the table below to find the regression equation, letting pizza cost be the predictor (x) variable. (Pizza cost is in dollars per slice, subway fare and CPI are in dollars.) What is the best predicted subway fare when pizza costs $4.01 per slice? Year Pizza Cost Subway Fare CPI 1960 1973 1986 1995 2002 2003 2009 2013 2015 2019 0.148 0.353 0.997 1.247 1.749 2.003 2.250 2.304 2.748 3.003 0.146 0.346 1.001 1.354 1.499 2.002 2.247 2.548 2.750 2.747 29.6 44.4 109.6 152.4 180.0 184.0 214.5 233.0 237.0 252.2 The regression equation is ŷ = + (x. (Round the y-intercept to four decimal places as needed. Round the slope to three decimal places as needed.)
Use the pizza cost and the subway fare in the table below to find the regression equation, letting pizza cost be the predictor (x) variable. (Pizza cost is in dollars per slice, subway fare and CPI are in dollars.) What is the best predicted subway fare when pizza costs $3.98 per slice? Year Pizza Cost Subway Fare CPI 1960 1973 1986 1995 2002 2003 2009 2013 2015 2019 0.152 0.353 1.000 1.251 1.753 2.003 2.254 2.300 2.747 2.997 0.151 0.346 1.000 1.347 1.497 2.004 2.253 2.551 2.747 2.750 29.6 44.4 109.6 152.4 180.0 184.0 214.5 233.0 237.0 252.2 The regression equation is y=+x. (Round the y-intercept to four decimal places as needed. Round the slope to three decimal places as needed.) The best predicted subway fare when pizza costs $3.98 per slice is $ (Round to the nearest cent as needed.)
In the below residual plot, which assumption(s) of regression is/are violated? -4 Residuals -2 0 2 Residuals vs Fitted 00 8080 00 08 810 300 049 -8 -6 -4 -2 -2 0 2 4 6 Fitted values Equal variance across levels of X Normality Residuals are independent Linear relationship between X and Y
Rewrite the regression model to include coefficients from your regression analysis output and then answer the following question What would be the company's loss if the significant variable(s) change per unit? SUMMARY OUTPUT Regression Statistics Multiple R 0.93082 R Square 0.866425 Adjusted R Square 0.85833 Standard Error 4108.993 Observations 36 ANOVA df SS MS F Significance F Regression 2 3.61E+09 1.81E+09 107.0261 3.75E-15 Residual 33 5.57E+08 16883824 Total 35 4.17E+09 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 3996.678 6603.651 0.605223 0.549171 -9438.55 17431.91 -9438.55 17431.91 X Variable 1 43.5364 3.589484 12.12887 1.05E-13 36.23354 50.83926 36.23354 50.83926 X Variable 2…
3. Regression analysis breaks scores on the DV into... (explain and give equations)
In this section, we introduced a descriptive measure of the utility of the regression equation for making predictions. a. Identify the term and symbol for that descriptive measure. b. Provide an interpretation.
Use the pizza cost and the subway fare in the table below to find the regression equation, letting pizza cost be the predictor (x) variable. (Pizza cost is in dollars per slice, subway fare and CPI are in dollars.) What is the best predicted subway fare when pizza costs $3.91 per slice? Year 1960 1973 1986 1995 2002 2003 2009 2013 2015 2019 Pizza Cost 0.153 0.347 0.998 1.247 1.751 1.996 2.246 2.298 2.751 2.997 Subway Fare 0.149 0.347 1.001 1.347 1.500 1.996 2.252 2.548 2.753 2.748 CPI 29.6 44.4 109.6 152.4 180.0 184.0 214.5 233.0 237.0 252.2 Question content area bottom Part 1 The regression equation is y=enter your response here+enter your response herex. (Round the y-intercept to four decimal places as needed. Round the slope to three decimal places as needed.) Part 2 The best predicted subway fare when pizza costs $3.91per slice is $enter…
Below is the output from regression. Use the p-value and decide if the equation is good to use for forecasting.

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