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Which variable age or sex has a higher proportional reduction of error?

Which variable age or sex has a higher proportional reduction of error?

MATLAB: An Introduction with Applications
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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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
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)
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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