Energy Consumption: A sample of ten households was monitored for one year. The household income (in $1000s) and the amount of energy consumed (1010 joules) were determined. The results follow. Income Energy Income Energy 31 40 28 48 195 16.0 40.2 29.8 45.6 184.6 96 70 100 145 78 98.3 93.8 77.1 114.8 67.0
Energy Consumption: A sample of ten households was monitored for one year. The household income (in $1000s) and the amount of energy consumed (1010 joules) were determined. The results follow. Income Energy Income Energy 31 40 28 48 195 16.0 40.2 29.8 45.6 184.6 96 70 100 145 78 98.3 93.8 77.1 114.8 67.0
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

Transcribed Image Text:Energy Consumption: A sample of ten households was monitored for one year. The household income (in
$1000s) and the amount of energy consumed (1010 joules) were determined. The results follow.
Income Energy Income Energy
a.
31
40
28
48
195
16.0
40.2
Intercept
Income
29.8
45.6
184.6
Multiple R
R Square
Adjusted R Square
Standard Error
Observations
96
70
100
145
78
98.3
93.8
The following output was obtained after performing regression analysis in Excel:
Regression Statistics
77.1
114.8
67.0
c. Interpret the value of the slope.
0.9598472
0.92130665
0.91146998
14.754434
10
coefficients
std. error
4.1659 8.940931
0.888239 0.091781 9.677832 0.00000522134
t (df-8)
0.325169
p-value
Lower 95%
0.753394 -17.710512
0.675
Give the value of the correlation coefficient and interpret its meaning.
Upper 95%
23.525136
1.095
b. Compute the least-squares regression line for predicting energy consumption () from income (x).
d. Predict the amount of energy consumption for a household with an income of $150,000. Round to the nearest
tenth.

Transcribed Image Text:e. What is the 95% confidence interval for the slope. You do not have to interpret the results.
f. Construct a 99% confidence interval for the slope. You do not have to interpret the results.
g- Test Ho: P₁ = 0 versus H₁: B₁ > 0. Can you conclude that income is useful in predicting energy consumption?
Use the a = 0.05 level of significance.
Is this a left-tailed test, a right-tailed test, or a two-tailed test?
ii.
iii.
iv.
V.
What is the value of the test statistic? Do not round.
Identify the p-value for this procedure. Do not round.
Using the p-value method, should Ho be rejected at the a = 0.05 level of significance? Why or why not?
Can you conclude that income is useful in predicting energy consumption?
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