Using Exhibit 15, answer the following questions. i) State and interpret the coefficient of the intercept. ii) Write the value of the coefficient of time and interpret it. iii) State and interpret the estimated coefficient for the second quarter. iv) State the quarter with the second highest total energy. State the value and interpret this value. v) Without stating the hypotheses for the test, determine if the total energy produced in Quarter 3 is different to the production in Quarter 4. Use a 1% level of significance and show all the steps. vi) Next, using this estimated model predict the total energy production for Quarter 3 in 2023. To do so: First, write down the value for the “Time” variable. [Hint: Time = 1 in Qtr 1 2014] Second, write down the value for each of the quarterly dummy variables for Quarter 3 2023. Third, write down the equation substituting these quarterly dummy values in the model (equation) to predict the total energy production for Quarter 3 2023.
Using Exhibit 15, answer the following questions.
i) State and interpret the coefficient of the intercept.
ii) Write the value of the coefficient of time and interpret it.
iii) State and interpret the estimated coefficient for the second quarter.
iv) State the quarter with the second highest total energy.
State the value and interpret this value.
v) Without stating the hypotheses for the test, determine if the total energy produced in Quarter 3 is different to the production in Quarter 4.
Use a 1% level of significance and show all the steps.
vi) Next, using this estimated model predict the total energy production for Quarter 3 in 2023. To do so:
First, write down the value for the “Time” variable. [Hint: Time = 1 in Qtr 1 2014]
Second, write down the value for each of the quarterly dummy variables for Quarter 3 2023.
Third, write down the equation substituting these quarterly dummy values in the model (equation) to predict the total energy production for Quarter 3 2023.
![SUMMARY OUTPUT
Regression Statistics
Multiple R
R Square
Adjusted R Square
Standard Error
Observations
ANOVA
Regression
Residual
Total
Intercept
Time
Q1
Q2
Q3
0.87673
0.76866
0.73881
162.6026
36
df
4
31
35
SS
Exhibit 15
MS
3E+06 680825.535
819627 26439.593
4E+06
Coefficients Standard Error
9211.6401
75.444
19.5573
2.624
77.055
494.984398
42.1156
76.831
299.4059
76.696
F
25.750
t Stat
122.09840 3.69E-43
7.45327 2.14E-08
6.42380 3.7E-07
0.54816 0.5875
3.90378 0.0005
Significance F
1.81E-09
P-value Lower 95% Upper 95%
9057.77
9365.51
14.20564
24.90896
337.8302
652.1386
-114.582
198.8135
142.9824 455.8294](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F508a77ab-0a17-47f4-81a6-47a24375402a%2Ff8bd605c-0368-46cf-9ab6-a660582b3819%2Fbdvnsf7_processed.png&w=3840&q=75)
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Comment: As per the our company guidelines we are supposed to answer only three subparts. Kindly repost other parts in the next question.
Solution:
Given information:
n= 36 observation
k= 4 independnet variables.
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