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A set of experimental runs were made to determine a way of predicting a parameter Z in terms of A and B. The results are represented in TABLE 1. 1) Using simple linear regression models, find the missing values in TABLE 1. 2) Using TWO (2) different methods, determine which independent variable is the most linearly related to the dependent variable? Show your calculations and discuss your results. 3) Using a multiple linear regression model, find the missing values in TABLE 1. Compare your results with those obtained in question 1) and discuss your findings. 4) Analyze and discuss the fitness of the multiple linear regression model for the data. TABLE 1. Z 22.1 12 16.5 17.9 7.2 11.8 9.2 19 22.4 12.5 24.4 11.3 14.6 18 A 37.8 45.9 a₁ 10.8 48.9 32.8 a2 32.9 47.7 36.6 39.6 20.5 23.9 27.7 16.7 27.1 B 69.2 69.3 58.5 58.4 75 23.5 65.9 46 52.9 b₁ 55.8 18.3 19.1 53.4 22.9 22.9 20.9 18.9 ************The End**

A set of experimental runs were made to determine a way of predicting a parameter Z in terms of A and B. The results are represented in TABLE 1. 1) Using simple linear regression models, find the missing values in TABLE 1. 2) Using TWO (2) different methods, determine which independent variable is the most linearly related to the dependent variable? Show your calculations and discuss your results. 3) Using a multiple linear regression model, find the missing values in TABLE 1. Compare your results with those obtained in question 1) and discuss your findings. 4) Analyze and discuss the fitness of the multiple linear regression model for the data. TABLE 1. Z 22.1 12 16.5 17.9 7.2 11.8 9.2 19 22.4 12.5 24.4 11.3 14.6 18 A 37.8 45.9 a₁ 10.8 48.9 32.8 a2 32.9 47.7 36.6 39.6 20.5 23.9 27.7 16.7 27.1 B 69.2 69.3 58.5 58.4 75 23.5 65.9 46 52.9 b₁ 55.8 18.3 19.1 53.4 22.9 22.9 20.9 18.9 ************The End**

Calculus For The Life Sciences
Calculus For The Life Sciences
2nd Edition
ISBN:9780321964038
Author:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.
Publisher:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.
Chapter1: Functions
Section1.EA: Extended Application Using Extrapolation To Predict Life Expectancy
Problem 5EA
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A set of experimental runs were made to determine a way of predicting a parameter Z in terms of A and B. The results are represented in TABLE 1. 1) Using simple linear regression models, find the missing values in TABLE 1. 2) Using TWO (2) different methods, determine which independent variable is the most linearly related to the dependent variable? Show your calculations and discuss your results. 3) Using a multiple linear regression model, find the missing values in TABLE 1. Compare your results with those obtained in question 1) and discuss your findings. 4) Analyze and discuss the fitness of the multiple linear regression model for the data. TABLE 1. Z 22.1 12 16.5 17.9 7.2 11.8 9.2 19 22.4 12.5 24.4 11.3 14.6 18 20.9 18.9 A 37.8 45.9 a₁ 10.8 48.9 32.8 B 69.2 69.3 58.5 58.4 75 23.5 65.9 46 52.9 b₁ 55.8 18.3 19.1 53.4 22.9 22.9 a2 32.9 47.7 36.6 39.6 20.5 23.9 27.7 16.7 27.1 **The End*
Transcribed Image Text:A set of experimental runs were made to determine a way of predicting a parameter Z in terms of A and B. The results are represented in TABLE 1. 1) Using simple linear regression models, find the missing values in TABLE 1. 2) Using TWO (2) different methods, determine which independent variable is the most linearly related to the dependent variable? Show your calculations and discuss your results. 3) Using a multiple linear regression model, find the missing values in TABLE 1. Compare your results with those obtained in question 1) and discuss your findings. 4) Analyze and discuss the fitness of the multiple linear regression model for the data. TABLE 1. Z 22.1 12 16.5 17.9 7.2 11.8 9.2 19 22.4 12.5 24.4 11.3 14.6 18 20.9 18.9 A 37.8 45.9 a₁ 10.8 48.9 32.8 B 69.2 69.3 58.5 58.4 75 23.5 65.9 46 52.9 b₁ 55.8 18.3 19.1 53.4 22.9 22.9 a2 32.9 47.7 36.6 39.6 20.5 23.9 27.7 16.7 27.1 **The End*
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