Which variable age or sex has a higher proportional reduction of error?
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
Which variable age or sex has a higher proportional reduction of error?
![a. Not assuming the null hypothesis.
b. Using the asymptotic standard error assuming the null hypothesis.
We take another look at the frequency of political discussions (DISCPOL), first presented in
Table 10.11 (based on GSS 2014). DISCPOL is presented with two independent variables-
12.
sex and (2) age (measured in categories as reported in corresponding tables).
(1) respondent
Interpret each measure of association. Which variable-age or sex-has a higher propor-
tional reduction of error?
Count
discpol HOW
OFTEN R DISCUSS
POLITICS
Total
discpol HOW OFTEN R DISCUSS POLITICS RAge recoded Age Crosstabulation
RAge recoded Age
2.00 30-39 3.00 40-49 4.00 50-59
Count
1 OFTEN
2 SOMETIMES
3 RARELY
4 NEVER
discpol HOW
OFTEN R DISCUSS
POLITICS
Total
Gamma
1.00 18-29
3
12
19
18
52
Symmetric Measures
Asymptotic
Standardized
Error
Value
-.206
260
Ordinal by
Ordinal
N of Valid Cases
a. Not assuming the null hypothesis.
b. Using the asymptotic standard error assuming the null hypothesis.
1 OFTEN
2 SOMETIMES
3 RARELY
4 NEVER
.070
discpol HOW OFTEN R DISCUSS POLITICS sex RESPONDENTS SEX
Crosstabulation
Approximate
TD
21
$7
49
32
159
5
17
25
31
78
sex RESPONDENTS SEX
1 MALE
2 FEMALE
-2.932
14
49
82
64
209
Total
35
106
131
96
368
4
16
23
15
58
Approximate
Significance
.003
8
26
24
14
72
Total
20
71
91
78
260
CHAPTER 10 The Chi-Square Test and Measures of Association](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fc8d37e0d-e4ba-4824-8046-15a7cedd1259%2F9ecd9bc1-4d70-4f27-87b3-e6857f4dbbc5%2F2r49y5_processed.jpeg&w=3840&q=75)
Transcribed Image Text:a. Not assuming the null hypothesis.
b. Using the asymptotic standard error assuming the null hypothesis.
We take another look at the frequency of political discussions (DISCPOL), first presented in
Table 10.11 (based on GSS 2014). DISCPOL is presented with two independent variables-
12.
sex and (2) age (measured in categories as reported in corresponding tables).
(1) respondent
Interpret each measure of association. Which variable-age or sex-has a higher propor-
tional reduction of error?
Count
discpol HOW
OFTEN R DISCUSS
POLITICS
Total
discpol HOW OFTEN R DISCUSS POLITICS RAge recoded Age Crosstabulation
RAge recoded Age
2.00 30-39 3.00 40-49 4.00 50-59
Count
1 OFTEN
2 SOMETIMES
3 RARELY
4 NEVER
discpol HOW
OFTEN R DISCUSS
POLITICS
Total
Gamma
1.00 18-29
3
12
19
18
52
Symmetric Measures
Asymptotic
Standardized
Error
Value
-.206
260
Ordinal by
Ordinal
N of Valid Cases
a. Not assuming the null hypothesis.
b. Using the asymptotic standard error assuming the null hypothesis.
1 OFTEN
2 SOMETIMES
3 RARELY
4 NEVER
.070
discpol HOW OFTEN R DISCUSS POLITICS sex RESPONDENTS SEX
Crosstabulation
Approximate
TD
21
$7
49
32
159
5
17
25
31
78
sex RESPONDENTS SEX
1 MALE
2 FEMALE
-2.932
14
49
82
64
209
Total
35
106
131
96
368
4
16
23
15
58
Approximate
Significance
.003
8
26
24
14
72
Total
20
71
91
78
260
CHAPTER 10 The Chi-Square Test and Measures of Association
![Nominal by
Nominal
Lambda
Goodman and
Kruskal tau
Gender
Male
Female
Total
Symmetric
discpol HOW
OFTEN R DISCUSS
POLITICS
Dependent
sex
Directional Measures
Indigenous status
Nonindigenous
Indigenous
RESPONDENTS
SEX Dependent
discpol HOW
OFTEN R DISCUSS
POLITICS
Dependent
sex
RESPONDENTS
SEX Dependent
Value
.058
.034
a. Not assuming the null hypothesis.
b. Using the asymptotic standard error assuming the null hypothesis.
C. Based on chi-square approximation
.094
1,146 (88.29)
156 (81.68)
1,302
.013
815 (87.17)
477 (88.17)
.039
Violent Offense Onset by Gender, Race, and Age
Asymptotic
Standardized
Error
.047
.043
.071
.007
.020
Approximate
Tb
1.213
.778
152 (11.71)
35 (18.32)
187
1.266
13. Paul Mazerolle, Alex Piquero, and Robert Brame (2010) examined whether violent onset
offenders have distinct career dimensions from offenders whose initial offending involves non-
violence. In this table, the researchers investigate the relationship between gender, race, and
age, and nonviolent versus violent onset using chi-square analysis. Their data are based on 1,503
juvenile offenders in Queensland, Australia. The independent variables are reported in rows.
120 (12.83)
Approximate
Significance
The chi-square models for gender and age at first offense are significant at the .01 level. Interpret
the relationship between gender and age at first offense with a nonviolent or violent initial offense.
.225
.437
206
.003
Nonviolent Onset N (%) | Violent Onset N (%) |_ Total N (%)
.002
1,298 (100)
191 (100)
1,489
x²=6.331**
935 (100)
41 (100)](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fc8d37e0d-e4ba-4824-8046-15a7cedd1259%2F9ecd9bc1-4d70-4f27-87b3-e6857f4dbbc5%2Frwbw32p_processed.jpeg&w=3840&q=75)
Transcribed Image Text:Nominal by
Nominal
Lambda
Goodman and
Kruskal tau
Gender
Male
Female
Total
Symmetric
discpol HOW
OFTEN R DISCUSS
POLITICS
Dependent
sex
Directional Measures
Indigenous status
Nonindigenous
Indigenous
RESPONDENTS
SEX Dependent
discpol HOW
OFTEN R DISCUSS
POLITICS
Dependent
sex
RESPONDENTS
SEX Dependent
Value
.058
.034
a. Not assuming the null hypothesis.
b. Using the asymptotic standard error assuming the null hypothesis.
C. Based on chi-square approximation
.094
1,146 (88.29)
156 (81.68)
1,302
.013
815 (87.17)
477 (88.17)
.039
Violent Offense Onset by Gender, Race, and Age
Asymptotic
Standardized
Error
.047
.043
.071
.007
.020
Approximate
Tb
1.213
.778
152 (11.71)
35 (18.32)
187
1.266
13. Paul Mazerolle, Alex Piquero, and Robert Brame (2010) examined whether violent onset
offenders have distinct career dimensions from offenders whose initial offending involves non-
violence. In this table, the researchers investigate the relationship between gender, race, and
age, and nonviolent versus violent onset using chi-square analysis. Their data are based on 1,503
juvenile offenders in Queensland, Australia. The independent variables are reported in rows.
120 (12.83)
Approximate
Significance
The chi-square models for gender and age at first offense are significant at the .01 level. Interpret
the relationship between gender and age at first offense with a nonviolent or violent initial offense.
.225
.437
206
.003
Nonviolent Onset N (%) | Violent Onset N (%) |_ Total N (%)
.002
1,298 (100)
191 (100)
1,489
x²=6.331**
935 (100)
41 (100)
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