temperature. (ii) Predict the electricity consumption of the office when the maximum temperature is 30°C. How confident are you in this prediction?

Managerial Economics: Applications, Strategies and Tactics (MindTap Course List)
14th Edition
ISBN:9781305506381
Author:James R. McGuigan, R. Charles Moyer, Frederick H.deB. Harris
Publisher:James R. McGuigan, R. Charles Moyer, Frederick H.deB. Harris
Chapter5: Business And Economic Forecasting
Section: Chapter Questions
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(i)
Find the least squares regression line to predict the electricity consumption from the maximum
temperature.
(ii)
Predict the electricity consumption of the office when the maximum temperature is 30°C. How
confident are you in this prediction?
Transcribed Image Text:(i) Find the least squares regression line to predict the electricity consumption from the maximum temperature. (ii) Predict the electricity consumption of the office when the maximum temperature is 30°C. How confident are you in this prediction?
Question 4 - Type Your Answers in Space Provided
(a)
An accountant wishes to undertake a cost analysis of electricity consumption of office heating
for various maximum daily temperatures. He recorded the data over a period of 8 random days,
as shown below:
2
3
4
5
6
8
Temp(°C)
Max Electricity Consumption
26
31
25
26
14
20
16
34
35
20
37
24
42
41
40
17
You may use the following Excel print-outs or summary statistics provided to answer the questions.
SUMMARY OUTPUT
SUMMARY STATISTICS
Regression Statistics
Multiple R
R Square
Adjusted R Square
Standard Error
n =
8.
0.895
24
0.801
32
0.768
s2x =
48.29
4.862
s?y =
101.71
%3!
Observations
8
Sxy =
-62.7143
Coefficient
Standard
Error
t Stat
P-value
6.575
Intercept
temp(°C)
63.172
9.607
0.000
-1.299
0.264
-4.911
0.003
Find the least squares regression line to predict the electricity consumption from the maximum
temperature.
Transcribed Image Text:Question 4 - Type Your Answers in Space Provided (a) An accountant wishes to undertake a cost analysis of electricity consumption of office heating for various maximum daily temperatures. He recorded the data over a period of 8 random days, as shown below: 2 3 4 5 6 8 Temp(°C) Max Electricity Consumption 26 31 25 26 14 20 16 34 35 20 37 24 42 41 40 17 You may use the following Excel print-outs or summary statistics provided to answer the questions. SUMMARY OUTPUT SUMMARY STATISTICS Regression Statistics Multiple R R Square Adjusted R Square Standard Error n = 8. 0.895 24 0.801 32 0.768 s2x = 48.29 4.862 s?y = 101.71 %3! Observations 8 Sxy = -62.7143 Coefficient Standard Error t Stat P-value 6.575 Intercept temp(°C) 63.172 9.607 0.000 -1.299 0.264 -4.911 0.003 Find the least squares regression line to predict the electricity consumption from the maximum temperature.
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