StatisticsStudent Name:University 11th January 2018
Descriptive StatisticsGender of the respondentsMajority of the respondents (54%, n = 13) were females with males being represented by 42% (n= 10). One person did not state the gender.Male or FemaleFrequencyPercentValid PercentCumulativePercentValid14.24.24.2Female1354.254.258.3Male1041.741.7100.0Total24100.0100.0In terms of the job category, most people were in production (38%, n = 9), closely followed by those in administration (33%, n = 8) while management represented 29% (n = 7).Job CategoryFrequencyPercentValid PercentCumulativePercentValidAdministration833.333.333.3Management729.229.262.5Production937.537.5100.0Total24100.0100.0Is there association between gender and job category?We sought to find out whether an association exists between gender and job category of therespondents. The following hypothesis was to be answered;H0: There is no significant association between job category and genderHA: There is significant association between job category and gender
To test this, a Chi-Square test of association (independence) was computed at 5% level ofsignificance. The results are given below.Job Category * Male or Female CrosstabulationCount Male or FemaleTotalFemaleMaleJob CategoryAdministration538Management347Production538Total131023Chi-Square TestsValuedfAsymp. Sig. (2-sided)Pearson Chi-Square.765a2.682Likelihood Ratio.7622.683N of Valid Cases23a. 6 cells (100.0%) have expected count less than 5. The minimum expected count is 3.04. As can be seen from the results above, the p-value for the Pearson Chi-Square test is 0.640 (avalue greater than 5% level of significance). We thus fail to reject the null hypothesis andconclude that there is no significant association between job category and gender at 5% level ofsignificance [ CITATION Dav071 \l 1033 ].
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