Fitting Logistic Reegression (depedent varaible(Employed), Independent variables (Age, Race.Ethnicities, Education.Attainment, gender) dataset Age Earnings Past 12...

Fitting Logistic Reegression (depedent varaible(Employed), Independent variables (Age, Race.Ethnicities, Education.Attainment, gender)

dataset

Age	Earnings Past 12 Months	Usual Weekly Hours	Female	Married	No High School Degree	High School Degree or GED	Some College	Associates Degree	Bachelors Degree	Masters Degree	Professional Degree	Doctorate	Educational Attainment	Employed	White	Black	American Indian or Native American	Asian	Hawaiian or Pacific Islander	Other Race	Biracial	Hispanic	Race/Ethnicity	Worked 40+ Weeks During Past 12 Months	Worked 35+ Hours in a Typical Week
18	1200	16	0	0	1	0	0	0	0	0	0	0	No High School Degree	1	1	0	0	0	0	0	0	0	White	0	0
53	0		1	0	0	1	0	0	0	0	0	0	High School Degree	0	0	0	0	0	0	0	0	1	Hispanic	0	0
61	0	70	0	1	0	0	1	0	0	0	0	0	Some College	1	1	0	0	0	0	0	0	0	White	1	1
32	350	24	1	0	0	0	1	0	0	0	0	0	Some College	1	1	0	0	0	0	0	0	0	White	0	0
49	0	30	0	0	0	0	0	0	0	1	0	0	Masters Degree	1	1	0	0	0	0	0	0	0	White	1	0

Solutions

Expert Solution

Hope the above answer has helped you in understanding the problem. Please upvote the ans if it has really helped you. Good Luck!!

orchestra answered 1 year ago

Next > < Previous

Related Solutions

Consider an earnings function with the dependent variable y monthly usual earnings and as independent variables...

Consider an earnings function with the dependent variable y monthly usual earnings and as independent variables years of education x1, gender x2 coded as 1 if female and 0 if male, and work experience in years x3. We are interested in the partial effect of years of education on earnings. We consider the following possible relations (that are assumed to be exact) y =β0 + β1x1 + β2x2 + β3x3 (1) y =β0 + β1x1 + β2x2 + β3x3 +...

The dataset flatulence.xlsx includes the variables gender, the self-reported number of times per day the respondent...

The dataset flatulence.xlsx includes the variables gender, the self-reported number of times per day the respondent passes gas (perday), and the number of months the respondent claims to wait before passing gas in front of a romantic partner (howlong). Find the 95% confidence interval for the average number of times a person passes gas in a day. Find the 99% confidence interval for: the average number of months a female waits before passing gas in front of a romantic partner,...

(Econometrics) Imagine you have a large dataset containing 12 variables on 5000 individuals over 12 year...

(Econometrics) Imagine you have a large dataset containing 12 variables on 5000 individuals over 12 year period. Individuals are interviewed annually and their income, assets, age, race, marriage status, sex, education level, mother's education, father's education, food expenditure, religion, and annual vacation spending are recorded. A) If you are trying to build a model predicting vacation spending what model would you build? B) Explain where you would prefer fixed effect vs random effects model. C) Should you worry about endogeneity?...

What are ways that gender and age can be variables that potentially can hold someone back...

What are ways that gender and age can be variables that potentially can hold someone back or get in the way? What stereotypes did you grow up with and how did you find that potentially limiting? What are some ways to decrease any limitations self-imposed or learned through families/friends to set yourself free of any gender or age barriers?

(3) Suppose that you run a regression of wage on a set of independent variables: age,...

(3) Suppose that you run a regression of wage on a set of independent variables: age, years of education, experience, and a dummy variable married. There are 100 observations, i.e., n=100. You want to test whether all the coefficient and intercept estimates in the equation for married and unmarried are equal to each other. i.e., Married: wage = β0 + β1*age + β2*educ + β3*exper + uUnmarried: wage = α0 + α1*age + α2*educ + α3*exper + v (a) Write...

Perform one correlation between two independent variables, such as Age and Relationship with Coworkers. Perform the...

Perform one correlation between two independent variables, such as Age and Relationship with Coworkers. Perform the second correlation on an independent variable (such as Relationship with Direct Supervisor) and the dependent variable (such as Workplace Happiness Rating. Gender Age Supervisor Telecommute Coworkers Happiness Engagement Overall Rating 1 29 1 1 2 7 8 15 2 32 4 1 3 9 10 19 1 39 1 1 1 4 5 8 1 25 2 1 2 5 8 13 1 27...

(I)Age (II)Physician Visits in the Past Year (III)Monthly Income (IV)Case Contacts in Past Year (V)Gender 74...

(I)Age (II)Physician Visits in the Past Year (III)Monthly Income (IV)Case Contacts in Past Year (V)Gender 74 8 $2,347 10 M 81 7 2,434 8 M 83 11 1,636 13 F 77 4 1,963 7 M 76 5 2,358 6 F 79 13 1,968 15 F 79 7 2,683 6 M 3. Suppose you are a caseworker for Eldergarden, an agency that provides social services to the elderly. You are assigned to provide some descriptive statistics for the agency's caseload for...

Subjects