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PS 225 Lecture 15 Analysis of Variance ANOVA Tables Analysis of Variance Compare the values of a variable when grouped according to the values of another variable Grouping variable called a ‘factor’ Differences Between Groups Observed sample differences caused by: True population differences Variation Different Types of Variance: Variation within groups Variation between group means Two Types of Variability With-in group variability Similar in concept to standard deviation Variability between the data in a sample Between-group variability Similar to the standard deviation of sample means Variation between sample means 4 6 8 Hours Spent at School Per Day 10 12 Box Plot Middle High School College Assumptions Needed for ANOVA Independent random samples taken from each population Normality Equality of Variance Levine Test Visual Examination of Box plot Comparing the Variation Types Between-Groups Mean Square Error Between-Groups Variation F = = Within-Groups Variation Division creates a ratio of the different types of variation Within-Groups Mean Square Error Mean Square Error A measure of variation Takes into account number of samples Within-Groups Sum of Squares Take standard deviation for all groups and square them to obtain variance Multiply each variance by the degree of freedom for each group (n-1) Between-Groups Sum of Squares Subtract the overall mean from each group mean and square the difference. Multiply the square by the number of observations in the group. Add all of the results to get the mean square Calculate the degrees of freedom- the number of groups minus 1 Divide the mean square by the degrees of freedom F-distribution Probability Distribution of the ratio of mean squares Small significance means reject Ho Ho: The mean is the same for all groups Why The F-Distribution? The more individual mean difference tests conducted, the greater the probability of observing a mean difference when there is none Conduct f-test to determine if there are differences Conduct Bonferroni multiple comparisons test to determine which means are different SPSS Anova Table Salary divided by Education Level SPSS Bonferroni Comparison Multiple Comparisons Dependent Variable: Current Salary Bonferroni (J) Employme nt (I) Employment Category Category Clerical Cus todial Manager Cus todial Clerical Manager Manager Clerical Cus todial Mean Difference (I-J) -$3,100.35 -$36,139.26* $3,100.35 -$33,038.91* $36,139.26* $33,038.91* *. The mean difference is s ignificant at the .05 level. Std. Error $2,023.760 $1,228.352 $2,023.760 $2,244.409 $1,228.352 $2,244.409 Sig. .379 .000 .379 .000 .000 .000 95% Confidence Interval Lower Bound Upper Bound -$7,962.56 $1,761.86 -$39,090.45 -$33,188.07 -$1,761.86 $7,962.56 -$38,431.24 -$27,646.58 $33,188.07 $39,090.45 $27,646.58 $38,431.24 Assignment What determines the age at which an individual is first married? Sex? Education (highest degree)? Determine if there are mean differences using an Anova table or Independent Sample T-test Determine which means are significantly different using the Boniferri Comparison when applicable Explain the relationship between all variable pairs, can you determine a specific cause of early marriage?