Question 28.14. From a sample of 209 firms, Wooldridge obtained the following regres-sion results":log (salary) = 4.32 + 0.280 log (sales) + 0.0174 roe + 0.00024 rosse = (0.32) (0.035)(0.0041)(0.00054)R = 0.283where salary = salary of CEOsales = annual firm salesroe = return on equity in percentros = return on firm's stockand where figures in the parentheses are the estimated standard errors.a. Interpret the preceding regression taking into account any prior expec-tations that you may have about the signs of the various coefficients.b. Which of the coefficients are individually statistically significant at the5 percent level?c. What is the overall significance of the regression? Which test do youuse? And why?d. Can you interpret the coefficients of roe and ros as elasticity coeffi-cients? Why or why not?

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Answered: Question 2 8.14. From a sample of 209…

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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A Moving to another question will save this response. Question 5 A straight-line fit y3 = e12) could be obtained with: A rectangular log plot of y versus with a slope of -2 and an intercept of -4 A rectangular plot of y versus with a slope of 6 and an intercept of -12 A rectangular plot of In y versus with a slope of 6 and an intercept of 12 None of the mentioned A semi log plot of y versus with a slope of 2 and an intercept of -4 A Moving to another question will save this response.
Question 2 Personal wealth tends to increase with age as older individuals have had more opportunities to earn and invest than younger individuals. The following data were obtained from a random sample of eight individuals and records their total wealth (Y) and their current age (X). Person Total wealth (‘000s of dollars) Age (Years) Y X A 280 36 B 450 72 C 250 48 D 320 51 E 470 80 F 250 40 G 330 55 H 430 72 A part of the output of a regression analysis of Y against X using Excel is given below: SUMMARY OUTPUT Regression Statistics Multiple R 0.954704 R Square 0.91146 Adjusted R Square 0.896703 Standard Error 28.98954…
Question 2 A regression was run to determine if there is a relationship between hours of study per week (x) and the final exam scores (y). The results of the regression were: y=ax+b a=6.992 b=38.9 > r²=0.779689 r=0.883 Use this to predict the final exam score of a student who studies 4 hours per week, and please round your answer to a whole number.
1.
Attempt 2 Question 5 of 10 Suppose a biologist studying the mechanical limitations of growth among different species of tulips monitors a national preserve. He collects data on the heights of 10 different types of tulips in the reserve and rounds each height to the nearest centimeter. 25, 21, 26, 24, 29, 34, 29, 25, 20, 23 Compute the first quartile (Q), the third quartile (Q3), and the interquartile range (IQR) of the data set. %3D cm cm Q3%D contact us help about us careers privacy policy terms of use 44 De
3
Questions 6-9. Consider the data in the table. Absolute Relative Percent Time Value Change Change Increase 13.60 1 17.00 21.25 26.56 4 33.20 5 41.50 Find the model for this data. y =13.60 *(1.25)^t y = 0.25 x + 13.60 y = 13.60 *(.25)^t y= 1.25 x+13.60
(a) In the manufacturing of a certain scientific instrument great importance is attached to the life of a particular critical component. This component is obtained in bulk from two sources, A and B, and in the course of inspection, the lives of 100 of the components from each source are determined. The following tables are obtained: - [3]Source ASource B Log xNo of componentsLog xNo of Components 1.72021.69901.67671.65321.62841.60211.57401122320191691.56821.62321.67211.71601.75591.79241.826113151728121005 Which source is more consistent?
10. You use the following four candidate models to fit a dataset with 300 observations. All parameters are estimated from the data. Model LogLikelihood SBC AIC Exponential Weibull -747 -753.704 Pareto -751 Gamma -747
QUESTION 3 We observe 10 components, starting from time t = 0. The component life times are independent. Observation ends immediately following the 7th failure, which occurs at time t = 13.48. Give (correct to 2 decimal places) an appropriate estimate for F(13.48), using the Mean ranking method.
QUESTION 1 Mr Stat was hired to do some research for the local potion master. He ran a Minitab analysis and found the regression equation for the age increase in years based on the quantity in milliliters, of Ageing Potion one consumed. Age Increase = 0.045*Quantity %3D a) What is the explanatory variable? Quantity b) What is the response variable? Age Increase Suppose the quantities in the st anged from 150ml to 740ml. If unable to predict, answer with n/a. c) How many years would someone's age increase if they drank 200ml? d) How many years would someone's age increase if they drank 100ml? n/a
G FTSE 100 6. Consider the OLS estimator of a model to explain the stock prices of observations from 2012 m1 to 2021 m 12, all variables are calculated company using 120 at the end of the month t log (stock +) 0.86 + 0.86 + 0.54 log (profit 6) - 0.65 log (research t)-1.34 log (marketing 6) (6.1) (1.12) (0.24) (0.30) (0.12) 3 n = 120, R² = 0.34 SSR = 1.29 F = 3.99 : / " 116 where stuck t the › in millions of stock price in GBP (British Sterling) profit & (the profit before tax GBP), research & (expenditure on research and development), and marketing t marketing) are measured in parentheses, SSR is the Sum of Squared Residuals, and the I statistic for the significance GBP. Standard errors are reported in (expenditure on millions of of the regression is $ provided. lat What is the interpretation of the coefficient on as you would expect? Explain your answer. log (profit t) 7 Is the sign of coefficient measured in thousands of GBP? Explain your answer. Hint: Would your interpretation…

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