117. The coefficient of correlation when coefficients of regressionand 1.8 is(a) 0.36(b) 0.2(c) 0.6(d) 0.9are 0.2

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Answered: 117. The coefficient of correlation…

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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Use the value of the linear correlation coefficient to calculate the coefficient of determination. What does this tell you about the explained variation of the data about the regression line? About the unexplained variation? r = -0.338 Calculate the coefficient of determination. (Round to three decimal places as needed.) % of the variation can be explained by the regression line (Round to one decimal place as needed.) % of the variation is unexplained and is due to other factors or to sampling error. (Round to one decimal place as needed.)
Q 1 If X is a random variable with distribution X: 0 1 2 3 P(X): 1111 44 44 Find the mean, Variance and standard deviation. Q 2 If X is a random variable with distribution X: 0 12 3 4 P(X): 0 K 2K 3K 4K Explain the following: (i) For which value of K, P(X) is probability mass function? (ii) Find the following probabilities: (a) P(1 ≤ X < 4). (b) P(2 < X < 4). Q3 A box contains 6 balls. Two are numbered 4, two are numbered 5, and two are numbered 6. The balls are mixed and one is selected at random. After a ball is selected, its number is recorded. Then it is replaced. If the experiment is repeated many times, find the variance (²) and standard deviation (o) of the numbers on the balls. Q4 A special six-sided die is made in which 2 sides have 6 spots, 3 sides have 4 spots, and 1 side has 1 spot. If the die is rolled, find the expected value of the number of spots that will occur. Q5 Let X-B(4,0.6). Find the following (i) P(X = 2) (ii) P(1 < X < 4) (iii) Also find mean and variance. Q6…
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If the R-squared for a regression model relating the outcome y to an explanatory variable x is 0.9. This implies that there is a positive linear relationship between y and x. True or false?
You run a regression analysis on a bivariate set of data (n = 51). You obtain the regression equation y=-4.028r+-18.476 with a correlation coefficient of r=-0.91 (which is significant at a = 0.01). You want to predict what value (on average) for the explanatory variable will give you a value of 170 on the response variable. What is the predicted explanatory value? X = (report 3 decimals)
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21. Which of the following statements is true regarding the sources of variation present in an analysis of regression? SSy is partitioned into variation explained by the regression model and residual variation. If most of the variability in Y is associated with residual variation, then X predicts Y. There are three sources of variation in an analysis of regression: regression variance, residual variance, and error variance. Regression variation measures variability in X, whereas residual variation measures variability in Y.
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A linear regression analysis reveals a strong, negative linear relationship between x and y. Which of the following could possibly be the results from this analysis? (A) ŷ 13.1 27.4x, r = 0.85 (B) == 27.4+ 13.1x, r = -0.95 (D) == (C) ŷ 13.1+ 27.4x, r = 0.95 542 385x, r = -0.15 (E) 0.85 0.25x, r = -0.85

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117. The coefficient of correlation when coefficients of regression and 1.8 is (a) 0.36 (b) 0.2 (c) 0.6 (d) 0.9 are 0.2