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=10,550.60+2781.63(Education)+870.46(Experience)Estimated Salary=10,550.60+2781.63(Education)+870.46(Experience)

Suppose an employee with 44 years of education has been with the company for 88 years (note that education years are the number of years after 8th8th grade). According to this model, what is his estimated annual salary?

0 0
Add a comment Improve this question Transcribed image text
Answer #1

Solution : From the given Data

Given regression model is

Estimated Salary : 10,550.60+2781.63(Education)+870.46(Experience)

Suppose an employee with 44 years of education has been with the company for 88 years then the estimated annual salary is

so Education = 44 years

Experience = 88 years

Estimated salary = 10,550.60+2781.63 (44) + 870.46 (88)

​​​​​​​ = 10550.60 + 122391.72 + 76600.48

= 209542.8

so, hence the estimated annual Salary = 209542.8

Add a comment
Know the answer?
Add Answer to:
Consider the following estimated regression model relating annual salary to years of education and work experience....
Your Answer:

Post as a guest

Your Name:

What's your source?

Earn Coins

Coins can be redeemed for fabulous gifts.

Not the answer you're looking for? Ask your own homework help question. Our experts will answer your question WITHIN MINUTES for Free.
Similar Homework Help Questions
  • 3. The table below shows the regression output of a multiple regression model relating the beginn...

    3. The table below shows the regression output of a multiple regression model relating the beginning salaries of employees in a given company to the following independent variables: Sex : an indicator variable (1=man and 0-woman) ducation years of schooling at the time of hire Experience number of months of previous work experience Source Regression Residual Total Df 4 8822,387,82 254,407 92 MS F-value 23.763,297 5,940,82423.35 46,151,118 Coefficient table Variable Constant Sex Education Experience Months t-value 10.94 6.02 3.22 2.16...

  • Question 1 1 pts Consider the following model for estimating the salary of employees at a company (in $) by the number of years employed at the company. technitron.1m-(salary- yrs.empl, data technitr...

    Question 1 1 pts Consider the following model for estimating the salary of employees at a company (in $) by the number of years employed at the company. technitron.1m-(salary- yrs.empl, data technitron.af) sumary(technitron.1n ss Call: # In(formula . salary ~ yrs.enp1. dat. . technitron.df) # Residuals: Medianax Min -12854.7-4188.9 281.5 3254.4 16493. a# as Coefficients Estimate Std. Error t value Pr( ltl) < 2e-16 5.93e-10 (Intercept) 28394.2 1107 .2 1794.อ 140.4 15.828 7.884 a: yrs . enp1 ㆅ signif. codes...

  • 4. Consider the following estimated semilog equation: = -8.10+ 0.100ED,+ 0.11 EXP where SAL = salary...

    4. Consider the following estimated semilog equation: = -8.10+ 0.100ED,+ 0.11 EXP where SAL = salary of the worker, ED = worker's years of education, and EXP = worker's years of experience. The mean salary is $50,000 and the mean education is 12 years. a. Interpret the estimated coefficients on education and experience. b. Calculate and interpret the slope and elasticity of salary with respect to education. c. Draw the shapes of the relationships between salary vs. education and salary...

  • Suppose the following data were collected from a sample of 15 CEOs relating annual salary to...

    Suppose the following data were collected from a sample of 15 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+ei . Is there enough evidence to support the claim that on average, CEOs in the industrial sector have lower salaries than CEOs in the financial sector at the 0.05 level of significance? If yes, write the regression equation in the spaces provided with...

  • Suppose the following table was generated from the sample data of 2020 employees relating annual salary...

    Suppose the following table was generated from the sample data of 2020 employees relating annual salary to years of education and gender. According to the results, is there a salary difference between men and women at the 0.050.05 level of significance? If yes, write the difference in salary in the space provided, rounded to two decimal places. Else, select "There is not enough evidence." Coefficients Standard Error t Stat P-Value Intercept −8619.401339−8619.401339 3672.4312293672.431229 −2.347056−2.347056 0.0312940.031294 Education 3622.7871453622.787145 231.963588231.963588 15.61791315.617913 0.0000000.000000...

  • Suppose the following table was generated from the sample data of 20 teachers relating annual salary...

    Suppose the following table was generated from the sample data of 20 teachers relating annual salary to months of teaching experience and gender. Coefficients Standard Error t Stat P-Value 7985.439824 304.553861 124.724867 0.000000 6.958001 11.888299 0.000000 Male (1 If male, 0 if female) 1420.439875 218.999146 6.486052 0.000006 Intercept 82.718798 Months of Experience Step 1 of 2: In this regression equation, what is the intercept value for women? Enter your answer in the space provided. Do not round your answer. 2...

  • A regression model relating number of salespersons at a branch office, to y, annual sales at...

    A regression model relating number of salespersons at a branch office, to y, annual sales at the office (in thousands of dollars) provided the following computer output from a regression analysis of the data. Where th =26. ANOVA SS MS F Significance F u Significance Regression Residual Total 8756.4 p-value 510 s.com Coefficients Standard Error Stat Intercept 7 7.0 10.723 Number of 5.609 Salespersons Write the estimated regression equation (to whole number). V= b. Compute the statistic and test the...

  • A regression model relating x, number of salespersons at a branch office, to y, annual sales...

    A regression model relating x, number of salespersons at a branch office, to y, annual sales at the office (in thousands of dollars) provided the following computer output from a regression analysis of the data. Where n total=26. a. Write the estimated regression equation (to whole number). y=_____+_____x b. Compute the F statistic and test the significance of the relationship at a .05 level of significance. (to 2 decimals) F-value ____ p-value is _______, we _________ h0 c. Compute the...

  • 1.13 Consider a multiple regression model 1.15 Consider a multiple regression model: with a dummy variable:...

    1.13 Consider a multiple regression model 1.15 Consider a multiple regression model: with a dummy variable: h(wage)-A, + β.educ + β white + β,NonWhite + u where wage and educ denote the annual income and the number of years of education, respectively. White indicates the dummy variable taking 1 if white and zero otherwisc. Non White indicates the dummy variable taking 1 if non-white (African, Hispanic, Asian, Pacific Islander, Native American, etc.) and zero otherwise. Which of the following is...

  • Question 3: Consider the following estimated quadratic regression model: Ý, = 0.5 + 0.03X, + 152i...

    Question 3: Consider the following estimated quadratic regression model: Ý, = 0.5 + 0.03X, + 152i + 0.52. where y = Individual Income, X Individual Education, and Z Age. Calculate the marginal effects (ME) of Y with respect to X and Z for a person with X - 2.5 (years) and Z -18 (years old); and explain clearly what these numbers for the ME's and the elasticities mean

ADVERTISEMENT
Free Homework Help App
Download From Google Play
Scan Your Homework
to Get Instant Free Answers
Need Online Homework Help?
Ask a Question
Get Answers For Free
Most questions answered within 3 hours.
ADVERTISEMENT
ADVERTISEMENT
ADVERTISEMENT