4) The following equation was estimated to explain sleeping patterns sleep = 3,638.25 -0,148 fotwork -11.13*...
Problem 2 (25 pts). The following multiple regression model is to study the tradeoff between time spent on sleeping and working and to look at other factors affecting sleep: sleep-a-bítoturk + bgeduc-b3age te where sleep and totwork (total work) are measured in minutes per week and educ and age are measured in years The estimated model is as follows. sleep3638.25 0.148 totwrk -11.13 educ + 2.2 age (5.88) (112.28) (0.017) n = 706, R-0.113 The standard error of each coefficient...
1. Consider the following equation where we report estimates along with their standard errors in brackets: =3683.25-0.148to twrk-11.13educ+ 2.20age (0.017) = 706, R2 = .113 sleep (5.88) (1.45) (112.28) n Dropping educ and age from the equation gives: sleep = 3586.38-0.151totwrk (38.91) n 706, R2 = .103 1.3. Are educ and age jointly significant in the original equation at 5% level? Explain. (1 point) (0.017)
1. Consider the following equation where we report estimates along with their standard errors in brackets: sleep = 3683.25-0.148totwrk - 11.13educ + 2.20age (0.017) = 706, R2 = .113 (1.45) (5.88) (112.28) 1.1. Use the t-statistics to find whether educ or age is individually significant at 5% level against a two- sided alternative? Show all the steps. (1 point)
Total 10 Points Assignment 4 1. Consider the following equation where we report estimates along with their standard errors in brackets: sleep = 3683.25 -0.148totwrk - 11.13educ +2.20age (112.28) (0.017) (5.88) (1.45) n = 706, R2 = .113 Name: . Construct the 90% and 99% confidence interval for the estimate of totwrk. Using the confidence ais, test the null hypothesis: H:B, = 0 against the alternative H.:B1 #0 at 10% and 1% level of significance (1 point). o borow bruilof...
This question refers to the question 1 in Exam 1 e sleep and totwork (total work) is measured in minutes per week and educ and age aremeasured in years, male is a dummy variable (male- 1 if the individual is male, and o if female) This is the STATA output of the model: 706 19.59 0.0000 0.1228 Adj R-squared0.1165 df MS Number of obs Model Residual 17092058.5 122147777 F (5, 700) 5 3418411.71 Prob>F 700 174496.825 R-squared Total 139239836 705...
Question 2 Consider the following estimated equation where sleep is the total weekly minutes spent sleeping, age is a person's age, female is a dummy variable that takes the value of 1 if the person is a female and 0 otherwise, and student is a dummy variable that takes the value of 1 if the person is a student and 0 otherwise. Standard errors are in parentheses. sleep = 1.47 - 2.52 age + 0.18 age? +0.721 female - 1.005...
Question 2 Consider the following estimated equation where sleep is the total weekly minutes spent sleeping, age is a person's age, female is a dummy variable that takes the value of 1 if the person is a female and 0 otherwise, and student is a dummy variable that takes the value of 1 if the person is a student and 0 otherwise. Standard errors are in parentheses. (1.02) sleep - 1.17 - 2.52 age + 0.18 age? +0.721 female -...
3. (4 marks) sleep = 3,840.83 - .163totwrk - 11.71educ - 8.79age +.128age2 + 87.75 male (235.11) (0.018) (5.86) (11.21) (0.134) (34.33) n=706, R2 = .123, R2 = .117 The variable sleep is total minutes per week spent sleeping at night, totwrk is total weekly minutes spent working, educ and age are measured in years, and male is a gender dummy. a. How do we interpret the intercept in this example? b. All other factors being equal, is there evidence...
ONLY NEES A,B help please!!!
1II. (10 pts) You are given the following estimated equation In(wage)- 0.3688+0.0852educ + 0.05 teure-0.000994tenue 0.0908) (0.0069) (0.0068) (0.00025) R-0.3294 526 in which: logtwage) log of average hourly wage; educ is the number of years of schooling tenure is the number of years of tenure fenure tenure remure The plot of the residuals against the fitted values from the regression above, is provided below: 2.5 1.5 Fitted values .5 a. With a 1% significance level,...
please be detailed in your response :) thank you!
0 pts) You are given the following estimated equation: In(wage) 0.1279+0.0904educ + 0.041 exper-0 (0.1059) (0.0075) (0.0052) (0.00012) R 0.3003 526 in which: log(wage) log of average hourly wage - educ is the number of years of schooling: - exper is the number of years of experience -exper'=experience"experience The plot of the residuals against the fitted values from the regression above, is provided below: .5 2.5 1.5 Fitted values a. With...