Solve the problem. An academic advisor wants to predict the typical starting salary of a graduate at a top business school using the GMAT score of the school as a predictor variable. A simple linear regression of SALARY versus GMAT using 25 data points is shown below. Po = -92040 51 = 228 s = 3213 r? = .66 r = .81 df = 23 t = 6.67 Give a practical interpretation of r = .81. O We estimate SALARY to increase 81% for every 1-point increase in GMAT. O We can predict SALARY correctly 81% of the time using GMAT in a straight-line model. O 81% of the sample variation in SALARY can be explained by using GMAT in a straight-line model. O There appears to be a positive correlation between SALARY and GMAT.
Solve the problem. An academic advisor wants to predict the typical starting salary of a graduate at a top business school using the GMAT score of the school as a predictor variable. A simple linear regression of SALARY versus GMAT using 25 data points is shown below. Po = -92040 51 = 228 s = 3213 r? = .66 r = .81 df = 23 t = 6.67 Give a practical interpretation of r = .81. O We estimate SALARY to increase 81% for every 1-point increase in GMAT. O We can predict SALARY correctly 81% of the time using GMAT in a straight-line model. O 81% of the sample variation in SALARY can be explained by using GMAT in a straight-line model. O There appears to be a positive correlation between SALARY and GMAT.
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question
Transcribed Image Text:Solve the problem.
An academic advisor wants to predict the typical starting salary of a graduate at a top business school using the GMAT score of the school
as a predictor variable. A simple linear regression of SALARY versus GMAT using 25 data points is shown below.
So = -92040 s1 = 228 s = 3213 r² = .66 r = .81 df = 23 t = 6.67
Give a practical interpretation of r = .81.
O We estimate SALARY to increase 81% for every 1-point increase in GMAT.
O We can predict SALARY correctly 81% of the time using GMAT in a straight-line model.
81% of the sample variation in SALARY can be explained by using GMAT in a straight-line model.
O There appears to be a positive correlation between SALARY and GMAT.
Expert Solution
This question has been solved!
Explore an expertly crafted, step-by-step solution for a thorough understanding of key concepts.
This is a popular solution!
Trending now
This is a popular solution!
Step by step
Solved in 2 steps
Recommended textbooks for you
MATLAB: An Introduction with Applications
Statistics
ISBN:
9781119256830
Author:
Amos Gilat
Publisher:
John Wiley & Sons Inc
Probability and Statistics for Engineering and th…
Statistics
ISBN:
9781305251809
Author:
Jay L. Devore
Publisher:
Cengage Learning
Statistics for The Behavioral Sciences (MindTap C…
Statistics
ISBN:
9781305504912
Author:
Frederick J Gravetter, Larry B. Wallnau
Publisher:
Cengage Learning
MATLAB: An Introduction with Applications
Statistics
ISBN:
9781119256830
Author:
Amos Gilat
Publisher:
John Wiley & Sons Inc
Probability and Statistics for Engineering and th…
Statistics
ISBN:
9781305251809
Author:
Jay L. Devore
Publisher:
Cengage Learning
Statistics for The Behavioral Sciences (MindTap C…
Statistics
ISBN:
9781305504912
Author:
Frederick J Gravetter, Larry B. Wallnau
Publisher:
Cengage Learning
Elementary Statistics: Picturing the World (7th E…
Statistics
ISBN:
9780134683416
Author:
Ron Larson, Betsy Farber
Publisher:
PEARSON
The Basic Practice of Statistics
Statistics
ISBN:
9781319042578
Author:
David S. Moore, William I. Notz, Michael A. Fligner
Publisher:
W. H. Freeman
Introduction to the Practice of Statistics
Statistics
ISBN:
9781319013387
Author:
David S. Moore, George P. McCabe, Bruce A. Craig
Publisher:
W. H. Freeman