ENGR.ECONOMIC ANALYSIS
14th Edition
ISBN: 9780190931919
Author: NEWNAN
Publisher: Oxford University Press
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Questions 1-30 refer to the following scenario: A company reports bi-annual (twice a year) sales data. The sales data for the last three years is shown in below Table.
The intercept (a) of the regressions line (DV: Sales, IV: Obs) is equal to
|
A
|
2 |
|
B
|
4 |
|
C
|
3 |
|
D
|
1 |
The slope (b) of the regressions line (DV: Sales, IV: Obs) is equal to
| a |
4 |
| b |
2 |
| c |
3 |
| d |
1 |
The standard error of the regression is
| a |
5.34 |
| b |
3.54 |
| c |
4.35 |
| d |
2.51 |
The standard error of the intercept is
| a |
1.30 |
| b |
2.30 |
| c |
0.30 |
| d |
3.30 |
You want to test the hypothesis that the intercept is statistically significantly different from zero. To do so, you use the attached t-table. Your alpha (the risk you accept to make a Type I error) is a=0.1. How many degrees of freedom do you have?
| a |
n |
| b |
n-2 |
| c |
4 |
| d |
both b. and c. are correct |
You want to test the hypothesis that the intercept is statistically significantly different from zero. To do so, you use the attached t-table. Your alpha (the risk you accept to make a Type I error) is a=0.1. What is your t-statistic to conduct the hypothesis test?
| a |
t=0.71 |
| b |
t=0.81 |
| c |
t=0.91 |
| d |
t=1.01 |
The standard error of the slope is
| a |
0.95 |
| b |
1.15 |
| c |
1.05 |
| d |
0.85 |
You want to test the hypothesis that the slope coefficient is statistically significantly different from zero. To do so, you use the attached t-table. Your alpha (the risk you accept to make a Type I error) is a=0.1. What is your t-statistic to conduct the hypothesis test?
| a |
4.35 |
| b |
3.35 |
| c |
2.35 |
| d |
1.35 |
Which statement is true? Given your alpha of a=0.1, you
| a |
Reject the null for the intercept, and fail to reject the null for the slope |
| b |
Reject the null for the slope, and fail to reject the null for the intercept |
| c |
Fail to reject the null for both the intercept and the slope |
| d |
Reject the null for both the intercept and the slope |
The explained sum of squares of the regression is ESS =
| a |
20 |
| b |
120 |
| c |
70 |
| d |
50 |
Transcribed Image Text:Year 1
Year 2
Year 3
Forecast
Year 4
Forecast
Year 5
Sales
25
24
23
22
21
20
19
18
17
16
15
14
13-
12
11
10
9
00
7
6
5
4
3
2
1
1
2
3
Bi-
Annual
Term
1
2
1
2
1
2
1
2
1
4
2
5
Obs Sales
("Xi") ("Yi")
1
2
3
4
5
609
7
8
10
7 8
6
3
13
9
16
13
10
10
XiYi Xi²(X-X₁²Ŷ (Y-Ŷ)² Y/Ŷ
Obs
Regression
Residual
Total
df S.S.
ANOVA
Seasonal Decomp.
Indices Forecast
Mean S.S.
Abs.
%
Errror
Significance
Note: In order to answer all questions, I recommend that
you fill out the above tables first. Please round all
answers to two digits only (e.g. 1.23).
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