Non Parametric Statistics

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Non Parametric Statistics Independent variables=Nominal or Ordinal Dependent variables=Nominal or Ordinal Chi square of association/Chi square of independence • Evaluates whether a statistical analysis exists between two variables when the variables are nominal/ordinal. • The rows represent the levels of one variable and the columns represent the levels of the other variable. What can I test with crosstabs • Relations between nominal/ordinal data – Religion and occupation – Sports participation and gender – Gender and virginity status – Personality Type from Mobil App & Personality Type from Questionnaire Example • Are proportions of male college students who treat young, middle age and elderly women the same • Personality has 2 levels – 0= Extraversion – 1= Introversion • Age of women has 3 levels – 1=young – 2=middle age – 3=elderly Click on Statistics Click on Cells Is there any relation between the Gender and Believer in God Status 9/27 = .33 = 33.3% 33.3% of females were Non-Believers Or 9/25 = .36=36% 36% of non- believers were females Use bar graph to display results Is there any relation between gender and belief in God? Results indicated a significant relationship between Gender and Belief in God (X2 (1, N=51) = 5.65, p = .017) and the effect size was moderate Ǿ= -.33. Females (66.7%) were more likely to be believers than males (33.3%). Interpreting effect Size- Cramer’s V = effect size for chi-square when you have more that 3 groups Phi coefficient= effect size for Effect size power based on degrees of freedom. The smallest side of chi-square= √ X2/N contingency table Effect Size .10 =small effect Smallest side of small medium large .30=moderate effect Contingency table 2 (df smaller=1) .10 .30 .50 .50=large effect Only use for 2 X 2 tables 3 (df smaller=2) .07 .21 .35 4 (df smaller=3) .06 .17 .29.

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