A large sample of data is collected in order to study the relationship between the two variables Xand Y to investigate whether X can be used to predict the value of Y. It is found that r= -75. Whichone of the following statements is true?X and Y are perfectly linear correlated and Y decreases as X increasesO X and Y are moderately linear correlated and Y increases as X increasesX and Y are perfectly linear correlated and Y increases as X increasesO X and Y are moderately linear correlated and Y decreases as X increases

A large sample of data is collected in order to study the relationship between the two variables X…

Answered: A large sample of data is collected in…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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The following statement contains an error. Choose the statement that best explains the error. "The correlation between shoe size and height is 0.87 inches" A. Correlation requires that both of the variables be categorical B. When stating the correlation coefficient, one must state whether it is a positive or negative relationship C. This statement does not tell us whether or not shoe size is correlated with height D. When reporting correlation, one does not report units because correlation has no units E. There is no error in this statement
Which of the following is true about the correlation coefficient? A) It ranges from 0 to 1. B) It indicates the strength and direction of a linear relationship between two variables. C) It can be greater than 1. D) It is used to measure the central tendency of data.
Compute the value of the multiple correlation (R). You should use a computer to find the solution. Y X1 X2 X3 27.6 1 4 4 9.4 3 5 3 15.6 4 7 1 20.3 5 5 4 12.3 3 7 3 8.7 5 3 6 7.3 7 5 7 14.9 6 4 8 17.0 5 3 9 -0.8 4 2 0
Which of the following correlation coefficients might lead a researcher to conclude that there is a weak, but significant, negative linear relation between variables X and Y? a. r=0.99 b. r=0.30 c. r=0 d. r=-0.30 c. r=-0.99
Q7
In a sample there are 3 male dogs and 3 female dogs. These dogs are couples such that the weight of the ith dog, and the Fi measures the weight of the ith dogs girlfriend. The correlation between M and F is exactly 1 and when the data points are graphed the slope of them are 1. Is it possible for some of these dogs to weight more than their female couple, while other dogs weight less then their female couple? And is it possible that all of the male dogs have couple female dogs that are all shorter than them?
A sample of 20 ordered pairs (x,y) has a value for "r" of r = 0.485 Which of the following statements are true? At the 5% level of significance, a positive correlation exists At the 1% level of significance, a positive correlation exists At the 1% level of significance, a negative correlation exists At the 5% level of significance, a negative correlation exists
This is a continuation of the last question I posted: f. The value of linear correlation coefficient r is i. 0.948 ii. 0.974 iii. -0.948 iv. -0.974 g.Based on your answer in part (f), the linear dependance between weekly exercise time and change in cholesterol level is strong negative i. True ii. False H. When weekly exercise time is 460 minutes (approximately 66 minutes per day), the 95 percent confidence interval for change in cholesterol level is (197.3, 225.4). This means that: i. If one person exercises 460 minutes per week, his/hers change in cholesterol level will be between 197.3 and 225.4 with 95 percent certainty.ii. If several people exercise 460 minutes per week, their average change in choles- terol level will be between 197.3 and 225.4 with 95 percent certainty. I. When weekly exercise time is 460 minutes (approximately 66 minutes per day), the 95 percent prediction interval for change in cholesterol level is (155.1, 267.6). This means that i. If one person…
3. If there is a linear, strong, and positive relationship between the scores on two tests, we should conclude that A. Scoring high on one test causes an individual to score high on the other test. B. high scores on one test are associated with low scores on the other test. C. as one test score goes down, the other test score goes up. D. low scores on one test are associated with low scores on the other test. E. the value of r must be close to 0.
Just need help with the last part as my answer is wrong. 115.6329 is also not right.

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