(a) Develop an estimated regression equation that can be used to predict Delay by using Industry and Quality. Use x₁ for Indus and x₂ for Quality. (Round your numerical values to two decimal places.) ŷ = (b) Plot the residuals obtained from the estimated regression equation developed in part (a) as a function of the order in which the data are presented. 30 20 O O Residuals 10+ 0- of -10- -20- -30 30 20 0 10- 0 -10+ -20+ -30 0 4 8 12 16 20 24 28 32 36 40 Order in Which Data Are Presented And 4 8 12 16 20 24 28 32 36 40 Order in Which Data Are Presented W Ho: P < 0 H₂: p=0 Ho: P = 0 Ha: p<0 1 Ho: P = 0 Ha: p > 0 O Ho: P>0 H₂: p=0 30 20 10- 00000 N -30 0 4 8 12 16 20 24 28 32 36 40 Order in Which Data Are Presented. -10- -20 30 20 10+ Manny www Does any autocorrelation appear to be present in the data? Explain. O The first 20 residuals show a pattern indicative of positive autocorrelation while the other 20 show a pattern indicative of negative autocorrelation. 0 -10- -20- -30 0 4 8 12 16 20 24 28 32 36 40 Order in Which Data Are Presented. Frequently a positive residual is followed by a negative residual in the next period, so there is no obvious pattern in the data indicative of positive autocorrelation. O The first 20 residuals show a pattern indicative of negative autocorrelation while the other 20 show a pattern indicative of positive autocorrelation. O Frequently a positive residual is followed by a positive residual in the next period, and a negative residual is followed by a negative residual in the next period, so there is a pattern in the data indicative of positive autocorrelation. (c) At the 0.05 level of significance, test for any positive autocorrelation in the data used in part (a). State the null and alternative hypotheses. 9 Find the value of the test statistic. (Round your answer to two decimal places.) What are the critical values? (Round your answers to two decimal places.) dL = du = ↑ State your conclusion. O Do not reject Ho. We conclude that there is no evidence of positive autocorrelation. O Reject Ho. We conclude that there is no evidence of positive autocorrelation. O Reject Ho. We conclude that there is significant positive autocorrelation. O Do not reject Ho. We conclude that there is significant positive autocorrelation. The test is inconclusive.
(a) Develop an estimated regression equation that can be used to predict Delay by using Industry and Quality. Use x₁ for Indus and x₂ for Quality. (Round your numerical values to two decimal places.) ŷ = (b) Plot the residuals obtained from the estimated regression equation developed in part (a) as a function of the order in which the data are presented. 30 20 O O Residuals 10+ 0- of -10- -20- -30 30 20 0 10- 0 -10+ -20+ -30 0 4 8 12 16 20 24 28 32 36 40 Order in Which Data Are Presented And 4 8 12 16 20 24 28 32 36 40 Order in Which Data Are Presented W Ho: P < 0 H₂: p=0 Ho: P = 0 Ha: p<0 1 Ho: P = 0 Ha: p > 0 O Ho: P>0 H₂: p=0 30 20 10- 00000 N -30 0 4 8 12 16 20 24 28 32 36 40 Order in Which Data Are Presented. -10- -20 30 20 10+ Manny www Does any autocorrelation appear to be present in the data? Explain. O The first 20 residuals show a pattern indicative of positive autocorrelation while the other 20 show a pattern indicative of negative autocorrelation. 0 -10- -20- -30 0 4 8 12 16 20 24 28 32 36 40 Order in Which Data Are Presented. Frequently a positive residual is followed by a negative residual in the next period, so there is no obvious pattern in the data indicative of positive autocorrelation. O The first 20 residuals show a pattern indicative of negative autocorrelation while the other 20 show a pattern indicative of positive autocorrelation. O Frequently a positive residual is followed by a positive residual in the next period, and a negative residual is followed by a negative residual in the next period, so there is a pattern in the data indicative of positive autocorrelation. (c) At the 0.05 level of significance, test for any positive autocorrelation in the data used in part (a). State the null and alternative hypotheses. 9 Find the value of the test statistic. (Round your answer to two decimal places.) What are the critical values? (Round your answers to two decimal places.) dL = du = ↑ State your conclusion. O Do not reject Ho. We conclude that there is no evidence of positive autocorrelation. O Reject Ho. We conclude that there is no evidence of positive autocorrelation. O Reject Ho. We conclude that there is significant positive autocorrelation. O Do not reject Ho. We conclude that there is significant positive autocorrelation. The test is inconclusive.
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
100%
Transcribed Image Text:(a) Develop an estimated regression equation that can be used to predict Delay by using Industry and Quality. Use x₁ for Industry
and x₂ for Quality. (Round your numerical values to two decimal places.)
ŷ =
(b) Plot the residuals obtained from the estimated regression equation developed in part (a) as a function of the order in which
the data are presented.
30
20
10-
of
-10
-20
-30
30
20
10
0
0
4 8 12 16 20 24 28 32 36 40
Order in Which Data Are Presented
-10+
-20 +
-30
0
4 8 12 16 20 24 28 32 36 40
Order in which Data Are Presented
MAT Ant
سلام
Ho: P < 0
H₁: p = 0
T
Ho: p = 0
Ha: p<0
30
Ho: P = 0
Ha: p > 0
20
10
Ho: p > 0
Ha: p = 0
0:
-10
-20
-30
30
20
04 8 12 16 20 24 28 32 36 40
Order in Which Data Are Presented
10-
of
0
-10+
-20
-30-
Does any autocorrelation appear to be present in the data? Explain.
O The first 20 residuals show a pattern indicative of positive autocorrelation while the other 20 show a pattern
indicative of negative autocorrelation.
0 4 8
● Frequently a positive residual is followed by a negative residual in the next period, so there is no obvious pattern in
the data indicative of positive autocorrelation.
O Frequently a positive residual is followed by a positive residual in the next period, and a negative residual is followed
by a negative residual in the next period, so there is a pattern in the data indicative of positive autocorrelation.
The first 20 residuals show a pattern indicative of negative autocorrelation while the other 20 show a pattern
indicative of positive autocorrelation.
12 16 20 24 28 32 36 40
Order in Which Data Are Presented Ⓡ
(c) At the 0.05 level of significance, test for any positive autocorrelation in the data used in part (a).
State the null and alternative hypotheses.
www.
↑
Find the value of the test statistic. (Round your answer to two decimal places.)
What are the critical values? (Round your answers to two decimal places.)
dL =
du =
State your conclusion.
O Do not reject Ho. We conclude that there is no evidence of positive autocorrelation.
O Reject Ho. We conclude that there is no evidence of positive autocorrelation.
O Reject Ho. We conclude that there is significant positive autocorrelation.
O Do not reject Ho. We conclude that there is significant positive autocorrelation.
The test is inconclusive.
Transcribed Image Text:A statistical program is recommended. You may need to use this table to answer this question.
A study investigated the relationship between audit delay (Delay), the length of time from a company's fiscal year-end to the date of
the auditor's report, and variables that describe the client and the auditor. Some of the independent variables that were included in
this study follow.
Industry
Public
Quality
Finished
62
45
A sample of 40 companies provided the following data.
54
Delay Industry Public Quality
71
91
62
61
2
69
80
52
47
65
60
81
73
89
71
76
68
68
86
76
67
57
55
54
69
82
94
74
75
69
71
79
80
91
92
46
A dummy variable coded 1 if the firm was an industrial company or 0 if the firm was a bank, savings and
loan, or insurance company.
72
A dummy variable coded 1 if the company was traded on an organized exchange or over the counter;
otherwise coded 0.
85
A measure of overall quality of internal controls, as judged by the auditor, on a five-point scale ranging
from "virtually none" (1) to "excellent" (5).
A measure ranging from 1 to 4, as judged by the auditor, where 1 indicates "all work performed
subsequent to year-end" and 4 indicates "most work performed prior to year-end."
0
0
。。。。。
0
0
0
0
0
0
0
0
0
0
0
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
0
1
0
1
0
0
0
1
0
0
0
1
0
0
0
0
0
0
0
0
0
1
0
0
1
0
0
0
0
1
1
0
0
0
0
0
0
1
0
0
3
3
2
1
1
4
3
5
1
5
3
2
1
1
2
2
5
2
1
5
2
3
2
4
3
5
3
5
1
5
4
2
4
5
1
4
1
4
5
5
Finished
1
3
2
2
1
4
2
2
1
3
2
3
3
2
2
1
4
2
2
2
2
1
3
2
2
2
3
1
1
2
3
2
4
2
4
1
4
3
2
1
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