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Independent t test in spss 16 how to#
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Business and Psychology Statistics Tuition in Sing.Hypothesis Testing and Confidence Interval Sample.Remember that if your data failed any of these assumptions, the output that you get from the independent t-test procedure (i.e., the tables we discuss below) will no longer be relevant and you will need to interpret these tables differently. If you expect that group 1 has a higher mean than group 2.
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First is to have an idea of which direction you want the t-statistic to go. The procedure for the one-tailed test is the same as for the two-tailed test. However, since you should have tested your data for these assumptions, you will also need to interpret the SPSS output that was produced when you tested for them (i.e., you will have to interpret: (a) the boxplots you used to check if there were any significant outliers (b) the output SPSS produces for your Shapiro-Wilk test of normality to determine normality and (c) the output SPSS produces for Levene's test for homogeneity of variances). SPSS has no specific procedure or dialog box to run a one-tailed test for differences of means. If your data passed assumption #4 (i.e., there were no significant outliers), assumption #5 (i.e., your dependent variable was approximately normally distributed for each group of the independent variable) and assumption #6 (i.e., there was homogeneity of variances), you will only need to interpret these two main tables. SPSS generates two main tables of output for the independent t-test.