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The data are from children between 5 and 9 years old. The variables are 1 = age in years y = Forced Exhalation Volume (FEV) (a measure of how much air somebody can forcibly exhale from their lungs) (Source: "An Exhalent Problem for Teaching Statistics", The Journal of Statistical Education, 13(2)) The summary statistics are as follows: n= 150, Ez =1139, Cu 314, = 8913, Ei = 694, Ez.m = 2441 i=1 i-1 Round all the numbers in your work and answers to TWO decimal places. (For each problem, you are supposed to show mathematical work.) 1. Complete the following chart. Syy Szy 2. Complete a chart for Parameter Estimates. Parameter Estimate t-value pvalue s.e. Intercept 0.0238 Slope 7.4 x 10-15 3. Write the fitted linear regression model for ŷ, in terms of r, Ân and ĝ1. For Å, and ŝ1, use the values you obtained in problem 2. 4. Complete a chart for ANOVA. Source df MS Fo pvalue Regression 7.4 x 10-15 Error Total 5. Find R° r, and s².

The data are from children between 5 and 9 years old. The variables are 1 = age in years y = Forced Exhalation Volume (FEV) (a measure of how much air somebody can forcibly exhale from their lungs) (Source: "An Exhalent Problem for Teaching Statistics", The Journal of Statistical Education, 13(2)) The summary statistics are as follows: n= 150, Ez =1139, Cu 314, = 8913, Ei = 694, Ez.m = 2441 i=1 i-1 Round all the numbers in your work and answers to TWO decimal places. (For each problem, you are supposed to show mathematical work.) 1. Complete the following chart. Syy Szy 2. Complete a chart for Parameter Estimates. Parameter Estimate t-value pvalue s.e. Intercept 0.0238 Slope 7.4 x 10-15 3. Write the fitted linear regression model for ŷ, in terms of r, Ân and ĝ1. For Å, and ŝ1, use the values you obtained in problem 2. 4. Complete a chart for ANOVA. Source df MS Fo pvalue Regression 7.4 x 10-15 Error Total 5. Find R° r, and s².

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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using the formula of regression analysis, to solve the problems

The data are from children between 5 and 9 years old. The variables are I = age in years y = Forced Exhalation Volume (FEV) (a measure of how much air somebody can forcibly exhale from their lungs) (Source: "An Exhalent Problem for Teaching Statistics", The Journal of Statistical Education, 13(2)) The summary statistics are as follows: n = 150, Ez = 1139, Ey = 314, x = 8913, Evi = 694, Ezy. = 2441 i-1 Round all the numbers in your work and answers to TWO decimal places. (For each problem, you are supposed to show mathematical work.) 1. Complete the following chart. Syy 2. Complete a chart for Parameter Estimates. Parameter Estimate t-value pvalue 8.e. Intercept 0.0238 Slope 7.4 x 10-15 3. Write the fitted linear regression model for in terms of r, Bo and B1. For Bo and B1, use the values you obtained in problem 2. 4. Complete a chart for ANOVA. Source df MS Fo pvalue Regression 7.4 x 10-15 Error Total 5. Find R2 r, and s?.
Transcribed Image Text:The data are from children between 5 and 9 years old. The variables are I = age in years y = Forced Exhalation Volume (FEV) (a measure of how much air somebody can forcibly exhale from their lungs) (Source: "An Exhalent Problem for Teaching Statistics", The Journal of Statistical Education, 13(2)) The summary statistics are as follows: n = 150, Ez = 1139, Ey = 314, x = 8913, Evi = 694, Ezy. = 2441 i-1 Round all the numbers in your work and answers to TWO decimal places. (For each problem, you are supposed to show mathematical work.) 1. Complete the following chart. Syy 2. Complete a chart for Parameter Estimates. Parameter Estimate t-value pvalue 8.e. Intercept 0.0238 Slope 7.4 x 10-15 3. Write the fitted linear regression model for in terms of r, Bo and B1. For Bo and B1, use the values you obtained in problem 2. 4. Complete a chart for ANOVA. Source df MS Fo pvalue Regression 7.4 x 10-15 Error Total 5. Find R2 r, and s?.
6. What is the residual e for the observation (x1, y1) = (9, 1.558)? 7. What is the conclusion for the test Ho : B1 = 0 vs Ho : B1 + 0 with a = 0.05? Why? 8. Find 95% confidence interval for B1. Use following table if you need. df taf,0.950 1.6555 1.6554 1.6553 taf,0.975 1.9764 1.9763 1.9762 1.9761 1.9760 45 46 47 48 49 50 1.6552 1.6551 1.6550 1.9759 9. Based on the linear regression model estimated above, what is the predicted value of yo, which is ŷo, when ro = 7.5?
Transcribed Image Text:6. What is the residual e for the observation (x1, y1) = (9, 1.558)? 7. What is the conclusion for the test Ho : B1 = 0 vs Ho : B1 + 0 with a = 0.05? Why? 8. Find 95% confidence interval for B1. Use following table if you need. df taf,0.950 1.6555 1.6554 1.6553 taf,0.975 1.9764 1.9763 1.9762 1.9761 1.9760 45 46 47 48 49 50 1.6552 1.6551 1.6550 1.9759 9. Based on the linear regression model estimated above, what is the predicted value of yo, which is ŷo, when ro = 7.5?
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