Question

Consider the following estimated regression model relating annual salary to years of education and work experience....

Consider the following estimated regression model relating annual salary to years of education and work experience. Estimated Salary=10,815.11+2563.46(Education)+897.49(Experience) . Suppose two employees at the company have been working there for five years. One has a bachelor's degree (8 years of education) and one has a master's degree (10 years of education). How much more money would we expect the employee with a master's degree to make?

Math   Statistics-And-Probability   
0 0
Add a commentTranscribed image text
Next >

Homework Answers

Answer #1

Estimated Salary=10,815.11+2563.46(Education)+897.49(Experience)

For Employee with bachelor's degree, Education = 8

For Employee with master's degree, Education = 10

The difference in education between Employee with master's degree and bachelor's degree = 10 - 8 = 2

Slope of the Education in estimated regression line = 2563.46

So, for same number of years of experience, employee with a master's degree will make 2 * 2563.46 = 5126.92 more than the employee with bachelor's degree.

0 0
Know the answer?
Your Answer:

Post as a guest

Your Name:

What's your source?

Earn Coins

Coins can be redeemed for fabulous gifts.

Log In

Sign Up

Not the answer you're looking for?
Ask your own homework help question
Similar Questions
Consider the following estimated regression model relating annual salary to years of education and work experience....
Consider the following estimated regression model relating annual salary to years of education and work experience. Estimated Salary=11,756.80+2723.3(Education)+1092.64(Experience) Suppose an employee with 11 years of education has been with the company for 2 years (note that education years are the number of years after  8th grade). According to this model, what is his estimated annual salary?
Consider the following computer output of a multiple regression analysis relating annual salary to years of...
Consider the following computer output of a multiple regression analysis relating annual salary to years of education and years of work experience. Regression Statistics Multiple R 0.7345 R Square 0.5395 Adjusted R Square 0.5195 Standard Error 2134.9715 Observations 49 ANOVA df SS MS F Significance F Regression 2 245,644,973.9500 122,822,486.9750 26.9460 1.8E-08 Residual 46        209,672,760.0092 4,558,103.4785 Total 48 455,317,733.9592 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 14271.51879 2,525.5672 5.6508 0.000000963 9187.8157 19,355.2219 Education (Years) 2351.3035...
Consider the following computer output of a multiple regression analysis relating annual salary to years of...
Consider the following computer output of a multiple regression analysis relating annual salary to years of education and years of work experience. Regression Statistics Multiple R 0.7338 R Square 0.5384 Adjusted R Square 0.5183 Standard Error 2139.0907 Observations 49 ANOVA df SS MS F Significance F Regression 2 245,472,093.5833 122,736,046.7917 26.8234 1.9E-08 Residual 46 210,482,624.6208 4,575,709.2309 Total 48 455,954,718.2041 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 14275.75637 2,530.4400 5.6416 0.000000994 9182.2448 19,369.2679 Education (Years) 2350.2675 338.3625...
Ford would like to develop a regression model that would predict the number of cars sold...
Ford would like to develop a regression model that would predict the number of cars sold per month by a dealership employee based on the employee's number of years of sales experience (X1), the employee's weekly base salary before commissions (X2), and the education level of the employee. There are three levels of education in the sales force—high school degree, associate's degree, and bachelor's degree. The following dummy variables have been defined. Degree X3 X4 High School 0 0 Associate's...
Suppose the following regression equation was generated from sample data relating salary to years of experience,...
Suppose the following regression equation was generated from sample data relating salary to years of experience, marital status, and the interaction term of years of experience and marital status. Marital status is a dummy variable where MARRIEDi=1MARRIEDi=1 if employee i is married and MARRIEDi=0MARRIEDi=0 if employee i is single. SALARYi=58316.795901+790.675473EXPERIENCEi+1222.075701MARRIEDi−36.766201EXPERIENCEiMARRIEDi+ei 1) In this regression equation, what is the intercept value for married employees? 2)In this regression equation, what is the value of the slope for married employees?
Suppose the following regression equation was generated from sample data relating annual salary to experience, gender,...
Suppose the following regression equation was generated from sample data relating annual salary to experience, gender, and marital status. Gender is represented by a dummy variable, FEMALEi where FEMALEi=1 if employee i is female and FEMALEi=0 if employee i is male. Marital status is represented by a dummy variable MARRIEDi where MARRIEDi=1 if employee i is married and MARRIEDi=0 if employee i is single. SALARYi=45399.358869+522.095299EXPERIENCEi−2445.498353FEMALEi−42.875876EXPERIENCEi⋅FEMALEi+10156.223595MARRIEDi−98.638952EXPERIENCEi⋅MARRIEDi−14314.347804FEMALEi⋅MARRIEDi+ei 1)According to the regression equation above, what is the estimated change in salary resulting from...
Based on a sample of 30 observations the population regression model to predict salary of employees...
Based on a sample of 30 observations the population regression model to predict salary of employees (dependent variable, numerical continuous) based on independent variables: education, measured as number of years of education (numerical, discrete but so many values), work experience, measured as number of years of work experience (numerical, continuous, for example 3.5 means 3 years 6 month work experience) department, department of the employee, There are three main departments in the organization (categorical nominal) Assume it affects only intercept...
Suppose the following regression equation was generated from sample data relating annual salary to experience, gender,...
Suppose the following regression equation was generated from sample data relating annual salary to experience, gender, and marital status. Gender is represented by a dummy variable, FEMALEiFEMALEi, where FEMALEi=1FEMALEi=1 if employee i is female and FEMALEi=0FEMALEi=0 if employee i is male. Marital status is represented by a dummy variable MARRIEDiMARRIEDi where MARRIEDi=1MARRIEDi=1 if employee i is married and MARRIEDi=0MARRIEDi=0 if employee i is single. SALARYi=46905.309796+429.685020EXPERIENCEi−2445.945436FEMALEi−35.464377EXPERIENCEi⋅FEMALEi+10084.736168MARRIEDi−60.572088EXPERIENCEi⋅MARRIEDi−14238.984644FEMALEi⋅MARRIEDi+eiSALARYi=46905.309796+429.685020EXPERIENCEi−2445.945436FEMALEi−35.464377EXPERIENCEi⋅FEMALEiSALARYi=+10084.736168MARRIEDi−60.572088EXPERIENCEi⋅MARRIEDi−14238.984644FEMALEi⋅MARRIEDi+ei According to the regression equation above, what is the estimated starting salary for married women?...
Consider the model ln(Yi)=β0+β1Xi+β2Ei+β3XiEi+ui, where Y is an individual's annual earnings in dollars, X is years...
Consider the model ln(Yi)=β0+β1Xi+β2Ei+β3XiEi+ui, where Y is an individual's annual earnings in dollars, X is years of work experience, and E is years of education. Consider an individual with a high-school degree (E=12yrs) who has been working for 20 years. The expected increase in log earnings next year (when X=21yrs) compared to this year is, dropping units, β1 β1+12β3 β1+β3 β0+21β1+12β2+252β3
Consider the following estimated multiple regression model relating GPA to the number of classes attended and...
Consider the following estimated multiple regression model relating GPA to the number of classes attended and the final exam score in a particular class, and if the student is a freshman (=1 if freshman, =0 otherwise). GPA = -0.3507+0.1096(Attendance) + 0.1697(Exam Score) -0.1380(Freshman) Suppose two students, one a junior and one a freshman, attended the same number of classes and both got a score of 88 on the final exam. What would be the expected difference in the GPa for...
ADVERTISEMENT
Need Online Homework Help?

Get Answers For Free
Most questions answered within 1 hours.

Ask a Question
ADVERTISEMENT