Exercise 6. Regression Fallacy. Historically, scores on the two midterms had a correlation of 0.48. Supposethat Jeri scored 2.1 standard deviations below the mean on the first midterm.(a) How many standard deviations [above or below?] the mean would you predict for her secondmidterm?

Introduction: Suppose X is the score on the first midterm, and Y is the score on the second midterm.

Answered: Exercise 6. Regression Fallacy.…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

See similar textbooks

Similar questions

Closing price of two stocks are recorded for 50 days. The sample standard deviation of stock X is 7.240 and the sample standard deviation of stock Y is 9.833. The sample covariance is -$22.075. What is the correlation coefficient?
If SST = 864, SSE = 494, SSxy = -20, and SSxx = 1.08 what is the value of the coefficient of correlation? 0.756 0.428 -0.654 -0.572
An r value of .8 indicates a strong positive correlation. True False
It is believed that standardized test scores, such as SAT, is a good predictor of first-year college students' GPA. 750 1200 3.2 1120 1000 1420 1280 1100 2.5 2.7 3.5 2.9 2.2 2.3 1. Find the p-value to determine if there is a linear correlation between SAT scores and GPA. Record the p- value below. Round to four decimal places. p-value = 2. Is there a linear correlation between SAT scores and GPA? 3. If there is a linear correation, write the correlation coefficient below. Otherwise, leave it blank. Round your final answer to four decimal places. T= 4. If there is a linear correlation, write the regression equation below. Otherwise, leave it blank. Round all numbers to four decimal places. 5. Using the data shown above, predict a student's first-year GPA when the student scores a 1275 on the SAT. Round your final answer to two decimal places. 6. If there is a linear correlation, what percentage of variation in GPAS can be explained by students' SAT scores? If there is not a linear…
A personality psychologist was interested in the relationship between height and income. They found there was a relationship and the effect size was: r = 0.08 in correlational units. Calculate a binomial effect size display(BESD) and then tell me what percentage of people who are tall (like me) you would predict to make more money than the average person. The correlation was randomly generated by eClass, so don't start daydreaming about how much or little you or I will make. Answer:
Which of the following is the strongest correlation? -0.90 +0.50 +0.95 -0.99
Suppose that the correlation between height and IQ in children is +0.70. What proportion (or percent) of the variability in IQ can be explained by the relationship with height? Select one: a. 44% b. 51% c. 70% d. 49%
The correlation coefficient between variables X and Y is 0.68. What does this signify? a. When X increases by 1, Y increases by 0.68 b. When Y increases 1, X increases by 0.68 c. The variance shared by X and Y is 68% d. The variance shared by X and Y is less 20%
Which scatter plot shown has the strongest negative correlation?
The correlation between a variable and itself is always equal to 0.5 -1 1
Which correlation coefficient best represents data that has a strong negative correlation? -0.95 O 0.05 0.05 O 0.95
A2. A study of test results at different schools shows that as the student-to-teacher ratio increases the average test result tends to decrease, although the relationship is quite weak. Which of the following is plausible value for the correlation between student-to- teacher ratio and average test results? A -0.9 B -0.3 C -0.01 D 0.3 E 0.9

SEE MORE QUESTIONS

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

SEE MORE TEXTBOOKS

Exercise 6. Regression Fallacy. Historically, scores on the two midterms had a correlation of 0.48. Suppose that Jeri scored 2.1 standard deviations below the mean on the first midterm. (a) How many standard deviations [above or below?] the mean would you predict for her second midterm?