Please answer the solution from the problem. Im very needed in 30 minutes thank u and no reject please. Thank u 3. Make a data analysis model using REGRESSION consisting ofsimple regression and multiple regression, accompanied by hypothesesand the basis for formulating scientific and complete hypotheses withsources!

Given information: PRICE # BED # BATH SQ. FOOT 349,000 3 1 1240 165,000 4 2 2619 369,900 3…

Answered: 3. Make a data analysis model using…

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018

18th Edition

ISBN:9780079039897

Author:Carter

Publisher:Carter

Chapter4: Equations Of Linear Functions

Section4.6: Regression And Median-fit Lines

Problem 4GP

See similar textbooks

Similar questions

Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s pole vault height has fallen below the value predicted by the regression line in Example 2. This might have occurred because when the pole vault was a new event there was much room for improvement in vaulters’ performances, whereas now even the best training can produce only incremental advances. Let’s see whether concentrating on more recent results gives a better predictor of future records. (a) Use the data in Table 2 (page 176) to complete the table of winning pole vault heights shown in the margin. (Note that we are using x=0 to correspond to the year 1972, where this restricted data set begins.) (b) Find the regression line for the data in part ‚(a). (c) Plot the data and the regression line on the same axes. Does the regression line seem to provide a good model for the data? (d) What does the regression line predict as the winning pole vault height for the 2012 Olympics? Compare this predicted value to the actual 2012 winning height of 5.97 m, as described on page 177. Has this new regression line provided a better prediction than the line in Example 2?
Find the equation of the regression line for the following data set. x 1 2 3 y 0 3 4
5. True or False? “Linear regression models are of no use when fitting polynomials and other non-linear patterns observed in the data." Explain.
The model developed from sample data that has the form of Yhat = bo +bjX is known as the multiple regression model with two predictor variables. (True or False) O True O False
What are the assumptions of multiple linear regressions only?
The marketing manager wants to test if the effect of the MBA program on salary depends on the work experience while controlling for the other factors. Which regression model is the MOST appropriate? O a. Salary = B_0+B_1 MBA+B_2 Work +B_3 Age +3_4 Gender + 8 Ob. Salary = B_0+ B_1 MBAx Work + B_2 Age + B 3 Gender & Oc. Salary = B_0+ B_1 MBA + B_2 MBA x Work + B_3 Age + B_4 Gender + e Od. Salary = B_0+ B_1 MBA+B_2 Work + B_3 MBA x Work + 3_4 Age + B_5 Gender + &
You are analyzing a dataset with 749 datapoints. You decide to create a linear regression model with this dataset, using 12 predictor variables. Using this information, what is the degrees of freedom associated with the sum of squares regression in your analysis?
Let’s assume a particular sample of Math classes contains several student GPAs from a minimum of 3.3 and a maximum of 4.0. The researcher would like to use a regression line to make estimations for future students who take this class and eventually graduate. Another student in a History class whose GPA is 3.1 would also like to use this regression line. (a) Can this regression line be used for the History student? Explain.
What do we mean when we say that a multiple regression model is a multiple linear regression model? What does “linear” mean here? Can we allow any “higher-order terms”? Explain.
(a) Demonstrate the two important things that should be done before one performs a regression analysis.
One problem that arises in multiple regression is the problem of multicollinearity i) What is multicollinearity? Explain with an example. Although multicollinearity is a serious problem in regressions econometricians claim it does not violate any of the underlying assumptions of the OLS model. (ii)True or False. (iii) Explain.
A business statistics professor would like to develop a regression model to predict the final exam scores for students based on their current GPAs, the number of hours they studied for the exam, the number of times they were absent during the semester, and their genders. The data for these variables are given in the accompanying table at the bottom of this page. a) Using Excel, construct a regression model using all of the independent variables. Create the dummy variable Gen, which equals 1 for a male and 0 for a female student ( this assignment is arbitrary) complete the regression equation for the model below, where y= Score, x1= GPA, x2= Hours, x3= Absenses, and x4= Gen. y= (__) + (__)x1 + (__)x2 + (__)x3 + (__)x4 b) Test the significance of the overall regression model using a= 0.10. c) interpret the meaning of the regression coefficient for the dummy variable. d) using the p-values, identify which independent variables are significant with a= 0.10. e) construct a regression…

SEE MORE QUESTIONS

Recommended textbooks for you

Glencoe Algebra 1, Student Edition, 9780079039897…

Algebra

ISBN:

9780079039897

Author:

Carter

Publisher:

McGraw Hill

Elementary Linear Algebra (MindTap Course List)

Algebra

ISBN:

9781305658004

Author:

Ron Larson

Publisher:

Cengage Learning

Functions and Change: A Modeling Approach to Coll…

Algebra

ISBN:

9781337111348

Author:

Bruce Crauder, Benny Evans, Alan Noell

Publisher:

Cengage Learning

Glencoe Algebra 1, Student Edition, 9780079039897…

Algebra

ISBN:

9780079039897

Author:

Carter

Publisher:

McGraw Hill

Elementary Linear Algebra (MindTap Course List)

Algebra

ISBN:

9781305658004

Author:

Ron Larson

Publisher:

Cengage Learning

Functions and Change: A Modeling Approach to Coll…

Algebra

ISBN:

9781337111348

Author:

Bruce Crauder, Benny Evans, Alan Noell

Publisher:

Cengage Learning

Big Ideas Math A Bridge To Success Algebra 1: Stu…

Algebra

ISBN:

9781680331141

Author:

HOUGHTON MIFFLIN HARCOURT

Publisher:

Houghton Mifflin Harcourt

College Algebra

Algebra

ISBN:

9781305115545

Author:

James Stewart, Lothar Redlin, Saleem Watson

Publisher:

Cengage Learning

Algebra and Trigonometry (MindTap Course List)

Algebra

ISBN:

9781305071742

Author:

James Stewart, Lothar Redlin, Saleem Watson

Publisher:

Cengage Learning

SEE MORE TEXTBOOKS

3. Make a data analysis model using REGRESSION consisting of simple regression and multiple regression, accompanied by hypotheses and the basis for formulating scientific and complete hypotheses with sources!