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Full data set The following data represent the heights and weights of various baseball players Height, x (inches) Player Nate Derek Mark Weight, y (pounds) Player Greg Randy Josh Pat Height, x (inches) Weight, y (pounds) 73 207 70 183 72 73 70 198 222 77 197 74 208 Jon 193 71 202 (a) Compute the least-squares regression line. y 4.5x- 125 (Do not round until the final answer. Then round to three decimal places as needed.) Compute the correlation coefficient. r0.9050 (Do not round until the final answer. Then round to four decimal places as needed.) (b) Remove the value corresponding to Randy and recompute the least-squares regression line. - (Do not round until the final answer. Then round to three decimal places as needed.) Remove the value corresponding to Randy and recompute the correlation coefficient. r= (Do not round until the final answer. Then round to four decimal places as needed.) (c) Do you think that Randy is an influential observation? Yes O No

Full data set The following data represent the heights and weights of various baseball players Height, x (inches) Player Nate Derek Mark Weight, y (pounds) Player Greg Randy Josh Pat Height, x (inches) Weight, y (pounds) 73 207 70 183 72 73 70 198 222 77 197 74 208 Jon 193 71 202 (a) Compute the least-squares regression line. y 4.5x- 125 (Do not round until the final answer. Then round to three decimal places as needed.) Compute the correlation coefficient. r0.9050 (Do not round until the final answer. Then round to four decimal places as needed.) (b) Remove the value corresponding to Randy and recompute the least-squares regression line. - (Do not round until the final answer. Then round to three decimal places as needed.) Remove the value corresponding to Randy and recompute the correlation coefficient. r= (Do not round until the final answer. Then round to four decimal places as needed.) (c) Do you think that Randy is an influential observation? Yes O No

MATLAB: An Introduction with Applications
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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Full data set The following data represent the heights and weights of various baseball players Height, x (inches) Player Nate Derek Mark Weight, y (pounds) Player Greg Randy Josh Pat Height, x (inches) Weight, y (pounds) 73 207 70 183 72 73 70 198 222 77 197 74 208 Jon 193 71 202 (a) Compute the least-squares regression line. y 4.5x- 125 (Do not round until the final answer. Then round to three decimal places as needed.) Compute the correlation coefficient. r0.9050 (Do not round until the final answer. Then round to four decimal places as needed.) (b) Remove the value corresponding to Randy and recompute the least-squares regression line. - (Do not round until the final answer. Then round to three decimal places as needed.) Remove the value corresponding to Randy and recompute the correlation coefficient. r= (Do not round until the final answer. Then round to four decimal places as needed.) (c) Do you think that Randy is an influential observation? Yes O No
Transcribed Image Text:Full data set The following data represent the heights and weights of various baseball players Height, x (inches) Player Nate Derek Mark Weight, y (pounds) Player Greg Randy Josh Pat Height, x (inches) Weight, y (pounds) 73 207 70 183 72 73 70 198 222 77 197 74 208 Jon 193 71 202 (a) Compute the least-squares regression line. y 4.5x- 125 (Do not round until the final answer. Then round to three decimal places as needed.) Compute the correlation coefficient. r0.9050 (Do not round until the final answer. Then round to four decimal places as needed.) (b) Remove the value corresponding to Randy and recompute the least-squares regression line. - (Do not round until the final answer. Then round to three decimal places as needed.) Remove the value corresponding to Randy and recompute the correlation coefficient. r= (Do not round until the final answer. Then round to four decimal places as needed.) (c) Do you think that Randy is an influential observation? Yes O No
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