produce a CROSSTAB for the variables SEX and FEFAM. Examine the relationship between these variables by testing both statistical significance and strength of association. Use chi-square for significance and choose the appropriate measures for strength of association (Phi, Cramer’s V, Lambda, or Gamma). Set alpha to .05. State the null and research hypotheses:H0:H1: What is the obtained chi-square value? What is the significance level (p-value) for the obtained chi-square? Should we reject or fail to reject the null hypothesis? Is there a statistically significant relationship between these variables? Which measure of association would be most appropriate for these variables? What is the value of the measure of association?Interpret your findings by explaining in full sentences whether there is a statistically significant relationship or not and the strength of the relationship. Also explain any patterns you see in the percentages: Respondents sex * Better for man to work, woman tend home CrosstabulationBetter for man to work, woman tend homeSTRONGLYSTRONGLYAGREEAGREEDISAGREEDISAGREETotalRespondents sexMALECount48182407189826% within Better for man to43.6%44.9%47.7%37.5%44.1%work, woman tend homeFEMALECount622234463151046% within Better for man to56.4%55.1%52.3%62.5%55.9%work, woman tend homeTotalCount1104058535041872% within Better for man to100.0%100.0%100.0%100.0%100.0%work, woman tend homeChi-Square TestsAsymptoticSignificance (2-Valuedfsided)Pearson Chi-Square13.548a3.004Likelihood Ratio13.6503.003Linear-by-Linear Association3.8331050N of Valid Cases1872a. O cells (0.0%) have expected count less than 5. The minimumD(Ctrl) -expected count is 48.54. Directional MeasuresAsymptoticApproximateValueStandard ErroreApproximate TSignificanceNominal by NominalLambdaSymmetric.000.000bRespondents sex Dependent.000.000Better for man to work, woman.000.000tend home DependentGoodman and Kruskal tauRespondents sex Dependent007.004.004Better for man to work, woman004.002000tend home Dependenta. Not assuming the null hypothesis.b. Cannot be computed because the asymptotic standard error equals zero.c. Based on chi-square approximationSymmetric MeasuresAsymptoticApproximateValueStandard Errore Approximate TbSignificanceNominal by NominalPhi.085004Cramer's V.085004Ordinal by OrdinalGamma.084.0372.250.024N of Valid Cases1872a. Not assuming the null hypothesis.b. Using the asymptotic standard error assuming the null hypothesis.

Given information: The SPSS output regarding the relationship between the variables SEX and FEFAM is…

Answered: produce a CROSSTAB for the variables…

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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produce a CROSSTAB for the variables SEX and FEFAM. Examine the relationship between these variables by testing both statistical significance and strength of association. Use chi-square for significance and choose the appropriate measures for strength of association (Phi, Cramer’s V, Lambda, or Gamma). Set alpha to .05.

State the null and research hypotheses:

H₀:

H₁:

What is the obtained chi-square value?

What is the significance level (p-value) for the obtained chi-square?

Should we reject or fail to reject the null hypothesis?

Is there a statistically significant relationship between these variables?

Which measure of association would be most appropriate for these variables?

What is the value of the measure of association?

Interpret your findings by explaining in full sentences whether there is a statistically significant relationship or not and the strength of the relationship. Also explain any patterns you see in the percentages:

Respondents sex * Better for man to work, woman tend home Crosstabulation
Better for man to work, woman tend home
STRONGLY
STRONGLY
AGREE
AGREE
DISAGREE
DISAGREE
Total
Respondents sex
MALE
Count
48
182
407
189
826
% within Better for man to
43.6%
44.9%
47.7%
37.5%
44.1%
work, woman tend home
FEMALE
Count
62
223
446
315
1046
% within Better for man to
56.4%
55.1%
52.3%
62.5%
55.9%
work, woman tend home
Total
Count
110
405
853
504
1872
% within Better for man to
100.0%
100.0%
100.0%
100.0%
100.0%
work, woman tend home
Chi-Square Tests
Asymptotic
Significance (2-
Value
df
sided)
Pearson Chi-Square
13.548a
3
.004
Likelihood Ratio
13.650
3
.003
Linear-by-Linear Association
3.833
1
050
N of Valid Cases
1872
a. O cells (0.0%) have expected count less than 5. The minimum
D(Ctrl) -
expected count is 48.54.

Directional Measures
Asymptotic
Approximate
Value
Standard Errore
Approximate T
Significance
Nominal by Nominal
Lambda
Symmetric
.000
.000
b
Respondents sex Dependent
.000
.000
Better for man to work, woman
.000
.000
tend home Dependent
Goodman and Kruskal tau
Respondents sex Dependent
007
.004
.004
Better for man to work, woman
004
.002
000
tend home Dependent
a. Not assuming the null hypothesis.
b. Cannot be computed because the asymptotic standard error equals zero.
c. Based on chi-square approximation
Symmetric Measures
Asymptotic
Approximate
Value
Standard Errore Approximate Tb
Significance
Nominal by Nominal
Phi
.085
004
Cramer's V
.085
004
Ordinal by Ordinal
Gamma
.084
.037
2.250
.024
N of Valid Cases
1872
a. Not assuming the null hypothesis.
b. Using the asymptotic standard error assuming the null hypothesis.

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