Ch 12 1-way ANOVA SPSS example Part 2 - Nov 15th

SPSS Example for 1-way ANOVA Harassment data set with school district employees Harassment data set with school district employees “School” variable indicates work setting “School” variable indicates work setting 1=elementary school 1=elementary school 2=middle school 2=middle school 3=high school 3=high school “Harassment in 1997” indicates har experiences from ’96-’97 “Harassment in 1997” indicates har experiences from ’96-’97 Does the work setting influence harassment experiences? Does the work setting influence harassment experiences?

(cont.) Get “anova_class” file from link on webpage Get “anova_class” file from link on webpage In SPSS menus: Analyze  Compare Means  One-way ANOVA In SPSS menus: Analyze  Compare Means  One-way ANOVA Then, “Dependent List” can indicate as many dependent variables as you’d like…here “Harassment in 1997” Then, “Dependent List” can indicate as many dependent variables as you’d like…here “Harassment in 1997” In “Factor” indicate the ‘grouping’ variable on which you’ll compare Harassment means… here “School” In “Factor” indicate the ‘grouping’ variable on which you’ll compare Harassment means… here “School”

(cont.) Click the “Options” button at bottom, click the box for Descriptives under “Statistics”, hit continue… Click the “Options” button at bottom, click the box for Descriptives under “Statistics”, hit continue… Click the “Post Hoc” button at bottom, click the box for “Bonferroni”, hit continue… Click the “Post Hoc” button at bottom, click the box for “Bonferroni”, hit continue… (this will give you output for follow-up comparisons in case your overall ANOVA is signif  if it’s not, you’ll ignore these comparisons) (this will give you output for follow-up comparisons in case your overall ANOVA is signif  if it’s not, you’ll ignore these comparisons) Now hit “OK” to run the analysis Now hit “OK” to run the analysis

Output You’ll have 3 sections of output… You’ll have 3 sections of output… The 1 st reports the group harassment means for elementary, middle, and high school employees The 1 st reports the group harassment means for elementary, middle, and high school employees You’ll need to look back at this to help w/interpretation in case your ANOVA is signif! You’ll need to look back at this to help w/interpretation in case your ANOVA is signif! 2 nd gives the overall ANOVA F test – for the null hypothesis of “no group differences” 2 nd gives the overall ANOVA F test – for the null hypothesis of “no group differences” Notice the MSBetween and MS Within, then the F statistic is your F obtained value, next to that is the “Sig” value Notice the MSBetween and MS Within, then the F statistic is your F obtained value, next to that is the “Sig” value If “Sig” value is <.05 (or.01 – depends on alpha)  Reject Null and conclude there are significant group differences If “Sig” value is <.05 (or.01 – depends on alpha)  Reject Null and conclude there are significant group differences

(cont.) But where are the signif group differences? Which groups differ? But where are the signif group differences? Which groups differ? 3 rd section gives follow-up comparisons (Bonferroni – but remember to use.05/3 =.017 as your new comparison alpha level) 3 rd section gives follow-up comparisons (Bonferroni – but remember to use.05/3 =.017 as your new comparison alpha level) Check each row for which pairs are being compared, then its “sig” value Check each row for which pairs are being compared, then its “sig” value If “sig” <.017 (or whatever your new alpha is)  Reject null of equal group means; conclude those 2 group means differ If “sig” <.017 (or whatever your new alpha is)  Reject null of equal group means; conclude those 2 group means differ Which schools significantly differ in harassment experiences? Which schools significantly differ in harassment experiences?