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A fire insurance company wants to relate the amount of fire damage in major residential fires to the distance between the residence and the nearest fire station. The study was conducted in a large suburb of a major city; a sample of fifteen recent fires in the suburb was selected. The amount of damage, y (£000), and the distance, r (km), between the fire and the nearest fire station are given in the following table. 2.3 3.1 y 26.2 17.8 31.3 23.1 27.5 36.0 14.1 22.3 1.1 y 19.6 31.3 24.0 17.3 43.2 36.4 26.1 * 3.4 1.8 4.6 5.5 0.7 3.0 2.6 4.3 2.1 6.1 4.8 3.8 (a) Fit a simple linear regression model to these data. Check if the residual plots give any reason to doubt the usual assumptions of the model.

A fire insurance company wants to relate the amount of fire damage in major residential fires to the distance between the residence and the nearest fire station. The study was conducted in a large suburb of a major city; a sample of fifteen recent fires in the suburb was selected. The amount of damage, y (£000), and the distance, r (km), between the fire and the nearest fire station are given in the following table. 2.3 3.1 y 26.2 17.8 31.3 23.1 27.5 36.0 14.1 22.3 1.1 y 19.6 31.3 24.0 17.3 43.2 36.4 26.1 * 3.4 1.8 4.6 5.5 0.7 3.0 2.6 4.3 2.1 6.1 4.8 3.8 (a) Fit a simple linear regression model to these data. Check if the residual plots give any reason to doubt the usual assumptions of the model.

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 fire insurance company wants to relate the amount of fire damage in major residential fires to the distance between the residence and the nearest fire station. The study was conducted in a large suburb of a major city; a sample of fifteen recent fires in the suburb was selected. The amount of damage, y (£000), and the distance, x (km), between the fire and the nearest fire station are given in the following table. 3.1 y 26.2 17.8 31.3 23.1 27.5 36.0 14.1 22.3 6.1 3.4 1.8 4.6 2.3 5.5 0.7 3.0 2.6 4.3 2.1 1.1 4.8 3.8 y 19.6 31.3 24.0 17.3 43.2 36.4 26.1 (a) Fit a simple linear regression model to these data. Check if the residual plots give any reason to doubt the usual assumptions of the model.
Transcribed Image Text:A fire insurance company wants to relate the amount of fire damage in major residential fires to the distance between the residence and the nearest fire station. The study was conducted in a large suburb of a major city; a sample of fifteen recent fires in the suburb was selected. The amount of damage, y (£000), and the distance, x (km), between the fire and the nearest fire station are given in the following table. 3.1 y 26.2 17.8 31.3 23.1 27.5 36.0 14.1 22.3 6.1 3.4 1.8 4.6 2.3 5.5 0.7 3.0 2.6 4.3 2.1 1.1 4.8 3.8 y 19.6 31.3 24.0 17.3 43.2 36.4 26.1 (a) Fit a simple linear regression model to these data. Check if the residual plots give any reason to doubt the usual assumptions of the model.
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