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

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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: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.
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?
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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