spss5 - Chapter 5 Analysis of variance SPSS Analysis of variance Data file used gss.sav How to get there Analyze Compare Means One-way ANOVA To test the

# spss5 - Chapter 5 Analysis of variance SPSS Analysis of...

This preview shows page 1 - 4 out of 6 pages.

Chapter 5 Analysis of variance SPSS –Analysis of variance Data file used: gss.sav How to get there: Analyze ° Compare Means ° ° One-way ANOVA … To test the null hypothesis that several population means are equal, based on the results of several independent samples. The test variable is measured on an interval- or ratio scale (for example age ), and is grouped by a variable which can be measured on a nominal or discrete ordinal scale (for example life existing of the categories Dull, Routine and Exciting). An independent T test and a one-way ANOVA for two independent samples test the same hypothesis . You must select the dependent variable, and specify the factor to define the different groups. You can move more than one variable into the Dependent List to test all of them. See following figure. Button ° Options … Here you can choose to get descriptives of the data (Descriptive), and to test for equal variances in the groups (Homogeneity-of-variance). Button ° Post Hoc … To see if, and if yes which, groups differ among themselves, there are several possibilities. You can use the Bonferroni procedure (see following figure) when there are equal variances in the groups, which can be tested with the Homogeneity-of-variance test ( Button ° Options) .
Output of running one-way ANOVA We performed a one-way ANOVA, with age as dependent variable, and life as factor, which exists of the groups: 0 = “Not applicable” 1 = “Dull” 2 = “Routine” 3 = “Exciting” 8 = “Don’t know” Oneway Descriptives Age of Respondent 65 52,62 20,059 2,488 47,64 57,59 19 89 457 47,28 18,191 ,851 45,61 48,95 19 89 471 44,54 16,106 ,742 43,08 46,00 18 87 993 46,33 17,479 ,555 45,24 47,42 18 89 Dull Routine Exciting Total N Mean Std. Deviation Std. Error Lower Bound Upper Bound 95% Confidence Interval for Mean Minimum Maximum Test of Homogeneity of Variances Age of Respondent 8,287 2 990 ,000 Levene Statistic df1 df2 Sig. ANOVA Age of Respondent 4492,439 2 2246,220 7,448 ,001 298568,2 990 301,584 303060,6 992 Between Groups Within Groups Total Sum of Squares df Mean Square F Sig. The table ‘Descriptives’ speaks for itself. In the table ‘Test of Homogeneity of Variances’ you find the result of Levene’s Test for Equality of Variances. It tests the condition that the variances of both samples are equal, indicated by the Levene Statistic. In this statistic, a high value results normally in a significant difference, in this example that is Sig . = 0,000. Strictly speaking, the Bonferroni procedure can therefore not be used, as it assumes equal variances.
However, we are dealing with large samples, which reduces the problem, and the Bonferroni test can be used and interpreted with care.

#### You've reached the end of your free preview.

Want to read all 6 pages?

• Spring '12
• rtgg

### What students are saying

• As a current student on this bumpy collegiate pathway, I stumbled upon Course Hero, where I can find study resources for nearly all my courses, get online help from tutors 24/7, and even share my old projects, papers, and lecture notes with other students.

Kiran Temple University Fox School of Business ‘17, Course Hero Intern

• I cannot even describe how much Course Hero helped me this summer. It’s truly become something I can always rely on and help me. In the end, I was not only able to survive summer classes, but I was able to thrive thanks to Course Hero.

Dana University of Pennsylvania ‘17, Course Hero Intern

• The ability to access any university’s resources through Course Hero proved invaluable in my case. I was behind on Tulane coursework and actually used UCLA’s materials to help me move forward and get everything together on time.

Jill Tulane University ‘16, Course Hero Intern