(a) Fit a simple linear regression model to the data using least squares method. (b) Find the proportion of variance of steam usage NOT explained by the temperature. (c) Conduct the hypothesis test: Ho: the slope b= 1 versus H1 : b > 1, at a = 0.05 level of significance. (d) Conduct the hypothesis test: Ho: the intercept a = 0 versus H1 : a # 0, at a = 0.01 level of significance.
(a) Fit a simple linear regression model to the data using least squares method. (b) Find the proportion of variance of steam usage NOT explained by the temperature. (c) Conduct the hypothesis test: Ho: the slope b= 1 versus H1 : b > 1, at a = 0.05 level of significance. (d) Conduct the hypothesis test: Ho: the intercept a = 0 versus H1 : a # 0, at a = 0.01 level of significance.
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question
The number of pounds of steam used per month at a plant is thought to be related to the average monthly ambient temperature (in ◦F). The past year’s usages and temperatures follow.
Transcribed Image Text:Temperature
Usage
Temperature
Usage
Month
( in °F)
(in 1000lb) | Month
( in °F)
(in 1000lb)
January
23
185.79
July
68
621.55
February
26
214.47
August
76
675.06
March
32
288.03
September
64
562.03
April
47
424.84
October
55
452.93
Мay
50
454.68
November
44
369.95
June
59
539.03
December
30
273.98
Transcribed Image Text:(a) Fit a simple linear regression model to the data using least squares method.
(b) Find the proportion of variance of steam usage NOT explained by the temperature.
(c) Conduct the hypothesis test: Ho: the slope b= 1 versus H1 :b > 1, at a =
0.05 level of significance.
(d) Conduct the hypothesis test: Ho: the intercept a = 0 versus Hị : a # 0, at a = 0.01 level of
significance.
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