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(a) Predict the mean test 2 score for entering freshmen who score a 23 on the test 1. O (Round to the nearest whole number as needed.) (b) Construct a 95% confidence interval for the mean test 2 score for entering freshmen who score a 23 on the test 1. The 95% confidence interval for the mean test 2 score for entering freshmen who score a 23 on the test 1 is lower bound: upper bound: (Round to the nearest whole number as needed) (c) Predict the test 2 score of a randomly selected freshman who scores a 23 on the test 1. O (Round to the nearest whole number as needed. ) (d) Construct a 95% prediction interval for the test 2 score for a randomly selected freshman who scores a 23 on the test 1. The 95% prediction interval for the test 2 score for a randomly selected freshman who scores a 23 on the test 1 is lower bound: O upper bound: (Round to the nearest whole number as needed.) (e) Explain why the predicted weights in parts (a) and (c) are the same, yet the intervals constructed in parts (b) and (d) are different. Choose the correct answer below. O A. The intervals are different because there is no linear relationship between test 1 scores and test 2 scores. O B. The intervals are different because the distribution of the mean weights, part (a), has more variability than the distribution of individual weights, part (c). OC. The intervals are different because the distribution of the mean weights, part (a), has less variability than the distribution of individual weights, part (c).

(a) Predict the mean test 2 score for entering freshmen who score a 23 on the test 1. O (Round to the nearest whole number as needed.) (b) Construct a 95% confidence interval for the mean test 2 score for entering freshmen who score a 23 on the test 1. The 95% confidence interval for the mean test 2 score for entering freshmen who score a 23 on the test 1 is lower bound: upper bound: (Round to the nearest whole number as needed) (c) Predict the test 2 score of a randomly selected freshman who scores a 23 on the test 1. O (Round to the nearest whole number as needed. ) (d) Construct a 95% prediction interval for the test 2 score for a randomly selected freshman who scores a 23 on the test 1. The 95% prediction interval for the test 2 score for a randomly selected freshman who scores a 23 on the test 1 is lower bound: O upper bound: (Round to the nearest whole number as needed.) (e) Explain why the predicted weights in parts (a) and (c) are the same, yet the intervals constructed in parts (b) and (d) are different. Choose the correct answer below. O A. The intervals are different because there is no linear relationship between test 1 scores and test 2 scores. O B. The intervals are different because the distribution of the mean weights, part (a), has more variability than the distribution of individual weights, part (c). OC. The intervals are different because the distribution of the mean weights, part (a), has less variability than the distribution of individual weights, part (c).

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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a,b,c

Using the sample data from the accompanying table, complete parts (a) through (e). Click the icon to view the data table. ... (a) Predict the mean test 2 score for entering freshmen who score a 23 on the test 1. (Round to the nearest whole number as needed.) (b) Construct a 95% confidence interval for the mean test 2 score for entering freshmen who score a 23 on the test 1 Data Table The 95% confidence interval for the mean test 2 score for entering freshmen who score a 23 on the test 1 is lower bound: upper bound: (Round to the nearest whole number as needed.) Full data set O (c) Predict the test 2 score of a randomly selected freshman who scores a 23 on the test 1. Test 1, x Test 2, y Test 1, x Test 2, y (Round to the nearest whole number as needed.) 18 1390 19 1470 1340 1910 1150 21 17 1190 (d) Construct a 95% prediction interval for the test 2 score for a randomly selected freshman who scores a 23 on the test 1. 27 28 1770 18 30 2290 The 95% prediction interval for the test 2 score for a randomly selected freshman who scores a 23 on the test 1 is lower bound: upper bound: 20 1360 20 1660 (Round to the nearest whole number as needed.) 25 1780 18 1480 25 1590 22 1370 (e) Explain why the predicted weights in parts (a) and (c) are the same, yet the intervals constructed in parts (b) and (d) are different. Choose the correct answer below. The least-squares regression equation is y = 63.1624x + 163.9988. O A. The intervals are different because there is no linear relationship between test 1 scores and test 2 scores. O B. The intervals are different because the distribution of the mean weights, part (a), has more variability than the distribution of individual weights, part (c). O C. The intervals are different because the distribution of the mean weights, part (a), has less variability than the distribution of individual weights, part (c). Print Done
Transcribed Image Text:Using the sample data from the accompanying table, complete parts (a) through (e). Click the icon to view the data table. ... (a) Predict the mean test 2 score for entering freshmen who score a 23 on the test 1. (Round to the nearest whole number as needed.) (b) Construct a 95% confidence interval for the mean test 2 score for entering freshmen who score a 23 on the test 1 Data Table The 95% confidence interval for the mean test 2 score for entering freshmen who score a 23 on the test 1 is lower bound: upper bound: (Round to the nearest whole number as needed.) Full data set O (c) Predict the test 2 score of a randomly selected freshman who scores a 23 on the test 1. Test 1, x Test 2, y Test 1, x Test 2, y (Round to the nearest whole number as needed.) 18 1390 19 1470 1340 1910 1150 21 17 1190 (d) Construct a 95% prediction interval for the test 2 score for a randomly selected freshman who scores a 23 on the test 1. 27 28 1770 18 30 2290 The 95% prediction interval for the test 2 score for a randomly selected freshman who scores a 23 on the test 1 is lower bound: upper bound: 20 1360 20 1660 (Round to the nearest whole number as needed.) 25 1780 18 1480 25 1590 22 1370 (e) Explain why the predicted weights in parts (a) and (c) are the same, yet the intervals constructed in parts (b) and (d) are different. Choose the correct answer below. The least-squares regression equation is y = 63.1624x + 163.9988. O A. The intervals are different because there is no linear relationship between test 1 scores and test 2 scores. O B. The intervals are different because the distribution of the mean weights, part (a), has more variability than the distribution of individual weights, part (c). O C. The intervals are different because the distribution of the mean weights, part (a), has less variability than the distribution of individual weights, part (c). Print Done
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