Question

Hello in an example where, I will use multiple regression to predict income based on educational...

Hello in an example where, I will use multiple regression to predict income based on educational attainment (having a high school diploma) and based on the occupation, would the dependent variable be "income" and the independent variables be "educational attainment" and "occupation?"

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

Homework Answers

Answer #1

Actually we can say that variables are dependent variables those which are used to predict a certain situation from the data based on independent variables. As your model is multiple regression so there should be more than one independent variables to predict the dependent variable. Here you want to predict income so it is the dependent variable and rest of those are independent variables. Obviously we can predict someone's income from educational attainment and occupation. Those who are having high qualifications obviously they will have a classy occupation and their salary should be higher than others. So income rate is high.

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
Think about a healthcare scenario where multiple regression might be useful in a healthcare organization. Consider...
Think about a healthcare scenario where multiple regression might be useful in a healthcare organization. Consider what your dependent and independent variables might be for conducting a multiple regression analysis. Build a small example, and run the regression analysis. Post a description of the dependent and independent variables you will use for your multiple regression analysis, and then explain your regression model in terms of your dependent and independent variables. Explain how you might measure your variables. Be specific and...
The owner of a movie theater company used multiple regression analysis to predict gross revenue (y)...
The owner of a movie theater company used multiple regression analysis to predict gross revenue (y) as a function of television advertising (x1) and newspaper advertising (x2). The estimated regression equation was ŷ = 82.5 + 2.26x1 + 1.30x2. The computer solution, based on a sample of eight weeks, provided SST = 25.3 and SSR = 23.415. (a)Compute and interpret R2 and Ra2. (Round your answers to three decimal places.) The proportion of the variability in the dependent variable that...
The owner of a movie theater company used multiple regression analysis to predict gross revenue (y)...
The owner of a movie theater company used multiple regression analysis to predict gross revenue (y) as a function of television advertising (x1) and newspaper advertising (x2).The estimated regression equation was ŷ = 83.1 + 2.23x1 + 1.30x2. The computer solution, based on a sample of eight weeks, provided SST = 25.4 and SSR = 23.395. (a) Compute and interpret R2 and Ra2. (Round your answers to three decimal places.) The proportion of the variability in the dependent variable that...
The owner of a movie theater company used multiple regression analysis to predict gross revenue (y)...
The owner of a movie theater company used multiple regression analysis to predict gross revenue (y) as a function of television advertising (x1)  and newspaper advertising (x2).  The estimated regression equation was ŷ = 83.8 + 2.26x1 + 1.50x2. The computer solution, based on a sample of eight weeks, provided SST = 25.8 and SSR = 23.385. (a) Compute and interpret  R2 and Ra2. (Round your answers to three decimal places.) The proportion of the variability in the dependent variable that can be...
1. For the following multiple regression which was conducted to attempt to predict the variable based...
1. For the following multiple regression which was conducted to attempt to predict the variable based on the independent variables shown, answer the following questions. Regression Statistics Multiple R 0.890579188 R Square 0.793131289 Adjusted R Square 0.7379663 Standard Error 30.28395534 Observations 20 ANOVA df SS MS F Regression 4 52743.23074 13185.81 14.37743932 Residual 15 13756.76926 917.1179509 Total 19 66500 Coefficients Standard Error t Stat P-value Intercept 73.33291 62.25276 1.17799 0.25715 X1 -0.13882 0.05353 -2.59326 0.02037 X2 3.73984 0.95568 3.91328 0.00138...
A multiple linear regression model based on a sample of 24 weeks is developed to predict...
A multiple linear regression model based on a sample of 24 weeks is developed to predict standby hours based on the total staff present and remote hours. The SSR is 31,193.47 and the SSE is 33,923.99. complete parts a through d. a. Determine whether there is a significant relationship between standby hours and the two independent variables at the .05 level of significance. test statistic pvalue state the conclusion b. Interpret the meaning of the p-value. c. compute the coefficent...
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...
We have developed a multiple regression model to predict the number of volunteers for a monthly...
We have developed a multiple regression model to predict the number of volunteers for a monthly charity event. One of the independent variables is Rain: a binary variable equal to 1 if it rains on the day of the event, and 0 otherwise. In the regression output, the coefficient for Rain is -22. What does that coefficient mean, precisely, with regard to the model’s predictions?
Would you use the Simple Linear Regression or Multiple Regression model to predict daily unit output?...
Would you use the Simple Linear Regression or Multiple Regression model to predict daily unit output? why?
Hello, I have computed a regression model where the dependent variable is "earn" as in how...
Hello, I have computed a regression model where the dependent variable is "earn" as in how much money the student will earn after college. My independent variables include "public" as in was this college public(1) or private(0), "academic ability" (a score calculated as the average score from SAT/ACT data of admitted students), "Average Cost" of tuition and  "population" (of the city the college is in). What is the impact on earnings of higher population of the college area/city? SUMMARY OUTPUT Regression...
ADVERTISEMENT
Need Online Homework Help?

Get Answers For Free
Most questions answered within 1 hours.

Ask a Question
ADVERTISEMENT