Consider the following diagnostics table from a multiple linear regression with 2 covariates: ID Standardized .h_ii DFFITS_i COVRATIO_i residual -1.2 0.172 -0.075 1.28 2 -0.4 0.1 0.546 1.009 0 0.206 0.431 1.281 4 -0.77 0.268 0.521 1.587 0.63 0.143 -0.355 1.183 1.58 0.132 -0.2 1.2 7 0.79 0.052 -0.073 1.114 8. 0.17 0.188 0.044 1.3 0.02 0.128 -0.186 1.2 10 -3.84 0.098 0.254 1.135 11 -0.4 0.09 -0.002 1.177 12 0.72 0.088 -0.015 1.165 13 0.03 0.17 -0.067 1.28 14 -0.58 0.12 0.11 -0.02 0.16 -0.25 1.21 15 1.241 16 -0.08 0.11 -0.03 1.197 17 -0.3 0.16 0.005 1.262 18 0.18 0.066 -0.571 0.884 19 1.16 0.198 1.66 0.782 20 0.35 0.335 -0.45 1.268 Use only two digits after the dot (eg, 1.23). For integers, just use the number, eg, 1. Do not write 'one'. If you think the space should be blank, just write NO in the space, Observation is an suggested bu ctan
Consider the following diagnostics table from a multiple linear regression with 2 covariates: ID Standardized .h_ii DFFITS_i COVRATIO_i residual -1.2 0.172 -0.075 1.28 2 -0.4 0.1 0.546 1.009 0 0.206 0.431 1.281 4 -0.77 0.268 0.521 1.587 0.63 0.143 -0.355 1.183 1.58 0.132 -0.2 1.2 7 0.79 0.052 -0.073 1.114 8. 0.17 0.188 0.044 1.3 0.02 0.128 -0.186 1.2 10 -3.84 0.098 0.254 1.135 11 -0.4 0.09 -0.002 1.177 12 0.72 0.088 -0.015 1.165 13 0.03 0.17 -0.067 1.28 14 -0.58 0.12 0.11 -0.02 0.16 -0.25 1.21 15 1.241 16 -0.08 0.11 -0.03 1.197 17 -0.3 0.16 0.005 1.262 18 0.18 0.066 -0.571 0.884 19 1.16 0.198 1.66 0.782 20 0.35 0.335 -0.45 1.268 Use only two digits after the dot (eg, 1.23). For integers, just use the number, eg, 1. Do not write 'one'. If you think the space should be blank, just write NO in the space, Observation is an suggested bu ctan
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Transcribed Image Text:Consider the following diagnostics table from a multiple linear regression with 2 covariates:
ID Standardized
h_i DFFITS i COVRATIO_i
residual
-1.2
0.172 -0.075
1.28
-0.4
0.1
0.546
1.009
3
0.206
0.431
1.281
4
-0.77
0.268
0.521
1.587
0.63
0.143 -0.355
1.183
6.
1.58
0.132
-0.2
1.2
7
0.79 0.052
-0.073
1.114
8
0.17
0.188
0.044
1.3
9.
0.02
0.128
-0.186
1.2
10
-3.84
0.098
0.254
1.135
11
-0.4
0.09 -0.002
1.177
12
0.72
0.088 -0.015
1.165
13
0.03
0.17 -0.067
1.28
14
-0.58
0.12
0.11
1.21
15
-0.02
0.16
-0.25
1.241
16
-0.08
0.11
-0.03
1.197
17
-0.3
0.16
0.005
1.262
18
0.18
0.066
-0.571
0.884
19
1.16
0.198
1.66
0.782
20
0.35
0.335
-0.45
1.268
Use only two digits after the dot (eg, 1.23).
For integers, just use the number, eg, 1. Do not write 'one'.
If you think the space should be blank, just write NO in the space,
Observation
is an
suggested by standardized residuals.
Transcribed Image Text:12
0.72
0.088
-0.015
1.165
13
0.03
0.17 -0.067
1.28
14
-0.58
0.12
0.11
1.21
15
-0.02
0.16
-0.25
1.241
16
-0.08
0.11
-0.03
1.197
17
-0.3
0.16
0.005
1.262
18
0.18
0.066
-0.571
0.884
19
1.16
0.198
1.66
0.782
20
0.35
0.335
-0.45
1.268
Use only two digits after the dot (eg, 1.23).
For integers, just use the number, eg, 1. Do not write 'one'.
If you think the space should be blank, just write NO in the space.
Observation
is an
suggested by standardized residuals.
The formal threshold (not the general 0.5 threshold) for detecting a high leverage point for this data is
Observation
is a high leverage point.
The threshold for detecting a suspicious point by DFFITS for this data is
Observation
is a/an
point suggested by DFFITS.
A suspicious point by COVRATIO should be smaller than
or bigger than
for this data set. You
need to write a formal threshold (not the general threshold of 1.)
By COVRATIO, observation
the precision. That means, it
(increases/decreases?)
the
of the point estimates of regression parameters.
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