3. The following model is a simplified version of the multiple regression model used by BESTEconometrics Group to study the trade off between time spent sleeping and working to look at otherfactors affecting sleep:sleep %3D Bo + Вitotwrk + Bzeduc + Bзадe + M,where sleep and totwork (total work) are measure in minutes per week and educ and age are measuredin years.(i) If adults trade sleep for work, what is the sign of B,?(ii) What signs do you think B2 and B3 wilI have?(iii) Using the data in SLEEP75.RAW, the estimated equation issleep— 3, 638.25—.148totwrk — 11.13educ — 2.20аge, п %3706, R? =. 113-If someone works five hours per week, by how manu minutes is sleep predicte d to fall? Is thisa large tradeoff?(iv) Discuss the sign and magnitude of the estimated coefficient on educ.(v) Would you say totwrk, educ, and age explain much of the variation in sleep? What other factorsmight affect the time spent sleeping? Are these likely to be correlated with totwrk?

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Answered: 3. The following model is a simplified…

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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Sometimes, the pattern of coefficients on the year dummy variables is itself of interest. For example, a demographer may be interested in the following question: After controlling for education, has the pattern of fertility among women over age 35 changed between 1972 and 1984? The following table illustrates how this question is simply answered by using multiple regression analysis with year dummy variables. The table below presents the results from a study carried out on the total number of kids born to a woman. The factors that are controlled for are years of education, age, race, region of the country where living at age 16, and living environment at age 16. Interpret the results of the estimated model provided above. and why can we not use first differences when we have independent cross sections in two years (as opposed to panel data)?
4. The following regression is fitted using variables identified that could be related to tuition charges ($) of a university. TUITION = a+ B ACCEPT + y MSAT + 1 VSAT Where ACCEPT = the percentage of applicants that was accepted by the university, MSAT = Median Math SAT score for the freshman class and VSAT = Median English SAT score for the freshman class. The data was processed using MNITAB and the following is an extract of the output obtained: Predictor Coef StDev T P Constant -26780 6115 -4.38 0.000 ACCEPT 116.00 37.17 * 0.003 MSAT -4.21 14.12 VSAT 70.85 15.77 -0.30 4.49 0.767 ** S = 2685 R-Sq = 69.6% Analysis of Variance R-Sq (adj) = 67.7% Source DF SS MS F P Regression 3 808139371 Residual Error 49 353193051 269379790 7208021 37.37 0.000 Total 52 1161332421 a) Write out the regression equation. b) State the dependent and independent variable(s) c) Fill in the blanks identified by ** and ****. d) Is B significant, at the 10% level of significance? e) State one limitation of using…
3. A Ross MAP team is trying to estimate the revenues of major-league baseball teams during the regular season using a regression model. Currently, the independent variables include stadium capacity, the number of weekend games, the number of night games, and the number of Wins (out of 162 regular season games). One of your team members suggests that the model also should include the number of losses as it provides additional explanatory power. Assume that ties are not possible; so every game results in exactly one team winning and the other team losing. Which of the following statements is the most likely conclusion of the new regression model? (a) R2 will increase, adjusted R2 will decrease, and Serror will decrease. (b) R2 and adjusted R2 will increase, and serror will decrease. (c) R, adjusted R2, and Serror will increase. (d) We cannot trust the regression output as some variables are highly correlated, resulting in multicollinearity. Answer to Question 3:
4. A study is conducted in patients with HIV. The primary outcome is CD4 cell count, which is a measure of the stage of the disease. Lower CD4 counts are associated with more advanced disease. The investigators are interested in the association between vitamin and mineral supplements and CD4 count. A multiple regression analysis is performed relating CD4 count to use of supplements (coded as 1 = yes, 0 = no) and to duration of HIV, in years (i.e., the number of years between the diagnosis of HIV and the study date). For the analysis, = CD4 count. = 501.41 + 12.67 Supplements – 30.23 Duration of HIV What is the expected CD4 count for a patient not taking supplements who has had HIV for 5 years? A) 350.26 B) 501.41 C) 30.23 D) 5
1. The following model is a simplified version of the multiple regression model used by Biddle and Hamermesh (1990) to study the tradeoff between time spent sleeping and working and to look at other factors affecting sleep: sleep = Bo + B1totwrk + Bzeduc + B3age + u, where sleep and totwrk (total work) are measured in minutes per week and educ and age are measured in years. (a) If adults trade off sleep for work, what is the sign of 31? (b) What signs do you think 32 and B3 will have? (c) Using the data in SLEEP75.csv, the estimated equation is sleep = 3638.25 – 0.148totwrk – 11.13educ + 2.20age, n = 706 R = 0.113. If someone works five more hours per week, by how many minutes is sleep predicted to fall? Is this a large tradeoff? (d) Discuss the sign and magnitude of the estimated coefficient on educ. (e) Would you say totwrk, educ, and age explain much of the variation in sleep? What other factors might affect the time spent sleeping? Are these likely to be correlated with totwrk? 2.…
If the R-squared for a regression model relating the outcome y to an explanatory variable x is 0.9. This implies that there is a positive linear relationship between y and x. True or false?
Fiske Corporation manufactures a popular regional brand of kitchen utensils. The design and variety has been fairly constant over the last three years. The managers at Fiske are planning for some changes in the product line next year, but first they want to understand better the relation between activity and factory costs as experienced with the current products. Discussions with the plant supervisor suggest that overhead seems to vary with labor-hours, machine-hours, or both. The following data were collected from last three year's operations: Quarter Machine-Hours 18,850 4 5 6 7 8 9 10 11 12 18,590 17,480 19,240 21,280 19,630 19,240 18,850 18,460 20,670 17,550 18,460 Labor-Hours 15,605 15,484 16,727 15,990 17,508 17,376 15,297 14,373 16,001 17,002 14,285 17,651 Factory costs $ 3,395,671 3,425,836 3,617,844 3,573,940 3,812,984 3,778,012 3,532,426 3,369,802 3,513, 187 3,731,434 3,325,615 3,724,486 Required: Prepare a scatter graph based on the factory cost and labor-hour data. Note: 1.…
A psychological study aimed at predicting Al Ain secondary school students’ mental health scores via their scores in the life satisfaction scale. The researcher examines the following null hypothesis: there is no significant relationship between Al Ain secondary school students’ mental health and their life satisfaction scores at 0.05 level of significance. Use the following data to establish the required regression equation. Student # Mental health score out of 50 Life- satisfaction score out of 100 1 40 80 2 41 87 3 34 90 4 30 78 5 44 89 6 42 85 7 45 88 8 32 77 9 47 90 10 22 57 11 30 78 12 28 77 13 35 76 14 40 84 15 31 76 16 39 80 17 41 84 18 24 60 19 22 50 20 37 75 21 40 80 22 38 78 23 29 60 24 24 55 25 24 62 26 29 61 27 32 65 28 34 66 29 28 67…
Suppose the following data were collected from a sample of 1515 CEOs relating annual salary to years of experience and the economic sector their company belongs to. Use statistical software to find the following regression equation: SALARYi=b0+b1EXPERIENCEi+b2SERVICEi+b3INDUSTRIALi+eiSALARY�=�0+�1EXPERIENCE�+�2SERVICE�+�3INDUSTRIAL�+��. Is there enough evidence to support the claim that on average, CEOs in the service sector have lower salaries than CEOs in the financial sector at the 0.010.01 level of significance? If yes, write the regression equation in the spaces provided with answers rounded to two decimal places. Else, select "There is not enough evidence." Copy Data CEO Salaries Salary Experience Service (1 if service sector, 0 otherwise) Industrial (1 if industrial sector, 0 otherwise) Financial (1 if financial sector, 0 otherwise) 144225144225 1010 11 00 00 187765187765 2020 00 00 11 142500142500 66 11 00 00 169650169650 2828 11 00 00 167250167250 3131 00…
1. Explain the purpose or use of the following:a. Linear regression equationb. Correlation coefficient.
When you are deciding which variables to include as predictors in a multiple regression equation, what are some conditions that you must consider first?
4. A study is conducted in patients with HIV. The primary outcome is CD4 cell count, which is a measure of the stage of the disease. Lower CD4 counts are associated with more advanced disease. The investigators are interested in the association between vitamin and mineral supplements and CD4 count. A multiple regression analysis is performed relating CD4 count to use of supplements (coded as 1 = yes, 0 = no) and to duration of HIV, in years (i.e., the number of years between the diagnosis of HIV and the study date). For the analysis, = CD4 count. Ÿ = 501.41 + 12.67 Supplements – 30.23 Duration of HIV What is the expected CD4 count for a patient not taking supplements who has had HIV for 5 years? A) 350.26 B) 501.41 C) 30.23 D) 5|

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