3/13/2021 0 Comments How To Do Levene'S Test In Spss
How to Levenes Statistic Test of Homogeneity of Variance Using SPSS.In homogeneity test research is used to determine whether or not there are similarities in the variance of a data group.Homogeneity tests are often found in parametric statistical analysis such as independent sample t test and ANOVA test.
The Selling data for Samsung and Lenovo mobile phones are shown in the following data. Open the new SPSS worksheet, then click Variable View to fill in the name and research variable property. Level with Levene Test section, select Power estimation, then click Continue. Note the third output, namely in the table Test of Homogeneity of Variance. The figure below illustrates this: watch the histograms become wider as the variances increase. You can ignore this assumption if you have roughly equal sample sizes for each group. However, if you have sharply different sample sizes, then you do need to make sure that homogeneity of variances is met by your data. And if these dont differ too much, then the population variances being equal seems credible. But at what point do we no longer believe the population variances to be all equal Levenes test tells us precisely that. If this is true, well probably find slightly different variances in our samples from these populations. However, very different sample variances suggests that the population variances werent equal after all. They test 2 supplements (a cortisol blocker and a thyroid booster) on 20 people each and another 40 people receive a placebo. All 80 participants have body fat measurements at the start of the experiment (week 11) and weeks 14, 17 and 20. This results in fatlossunequal.sav, part of which is shown below. Perhaps a better approach to these data is using a single repeated measures ANOVA. Weeks would be the within-subjects factor and supplement would be the between-subjects factor. For now, well leave it as an exercise to the reader to carry this out. Since weve unequal sample sizes, we need to make sure that each supplement group has the same variance on each of the 4 measurements first. The easiest way to go -especially for multiple variables- is the One-Way ANOVA dialog. The main limitation of the One-Way ANOVA dialog is that it doesnt include any measures of effect size. For more on this, see How to Get (Partial) Eta Squared from SPSS. ONEWAY fat11 fat14 fat17 fat20 BY condition STATISTICS DESCRIPTIVES HOMOGENEITY MISSING ANALYSIS. The second -shown below- is the Test of Homogeneity of Variances. For the last 2 variables, p: for fat percentages in weeks 17 and 20, we reject the null hypothesis of equal poplation variances. So these 2 variables violate the homogeity of variance assumption needed for an ANOVA. A sound way for evaluating if this holds is inspecting the Descriptives table in our output. Because theyre not (roughly) equal, we do need the homogeneity of variance assumption but its not met by 2 variables. In this case, well report some alternative results ( Welch and Games-Howell ) but these are beyond the scope of this tutorial.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |