**Group Statistics**- Variable: 171C04(R): Rs RACE B/W/H| Category | N | Mean | Std. Deviation | Std. Error Mean ||------------|------|------|----------------|-----------------|| BLACK (1) | 1488 | 2.43 | 1.843 | 0.048 || WHITE (2) | 6356 | 3.61 | 2.279 | 0.029 |**Independent Samples Test**- Variable: BY17 00810 #X DRNK/LIFETIME| Test Type | Levene's Test for Equality of Variances | t | df | Sig. (2-tailed) ||------------------------------------|----------------------------------------|---------|----------|----------------|| | F | Sig. | | | || Equal variances assumed | 300.885| 0.000 | -18.704 | 7842 | 0.000 || Equal variances not assumed | | | -21.309 | 2661.631 | 0.000 |**Explanation of the Tables:**1. **Group Statistics Table**: This table presents the sample size (N), mean, standard deviation, and standard error mean for two racial groups (Black and White) in relation to the variable BY17 00810 #X DRNK/LIFETIME.2. **Independent Samples Test Table**: This section provides results of a t-test comparing the two racial groups. It includes Levene’s Test for Equality of Variances with its F and Sig. values, showing whether equal variances can be assumed. The test then provides t values, degrees of freedom (df), and significance (Sig. 2-tailed), indicating if there's a statistically significant difference between the means of the two groups.These tables are often used in educational contexts to teach statistical analysis, particularly in understanding mean differences and variance between different groups. **C10.** In this SPSS output, we examine lifetime use of alcohol among white and black students based on the MTF 2017. Lifetime use is measured on an ordinal scale: 1 = 0 occasions, 2 = 1–2 times, 3 = 3–5 times, 4 = 6–9 times, 5 = 10–19 times, 6 = 20–39 times, and 7 = 40+. Present Step 5 (final decision) for these data. Assume alpha = .05, two-tailed test.

Before comparing the means of two groups, first verify one of the important assumptions of performing the t-test, i.e. homogeneity of variances. If the assumption is satisfied, then the pooled t-test will be more appropriate, else the independent t-test will be more appropriate. State the null and the alternative hypothesis: H0: Two populations have equal variances. H1: Two populations do not have equal variances. From Levene's Test for Equality of Variances, the computed F statistic is 300.885 and the corresponding p-value is 0.000. Since the p-value of the test 0.000 is less than the level of significance 0.05; therefore, the null hypothesis gets rejected. Hence, there is sufficient evidence to conclude that the two populations do not have equal variances. The null hypothesis is a simple statement about the value of the population parameter which is liable to be rejected. It always contains an equal sign.An alternative hypothesis is simply the contradiction of the null hypothesis. It is the statement that is claimed by the researcher in the study.This is an example of a two-tailed test as the researcher is interested in knowing whether the mean lifetime use of alcohol among white and black students is the same or not. State the null and the alternative hypothesis. H0: The mean lifetime use of alcohol among white and black students is the same. H1: The mean lifetime use of alcohol among white and black students is not the same. From the table of Independent Samples Test, the value of the t-statistic when equal variances are not assumed is t=-21.309 and the corresponding p-value for the test in the last column of the table is 0.000. Since the p-value of the test 0.000 is less than the level of significance 0.05; therefore, the null hypothesis gets rejected. Hence, there is sufficient evidence to conclude that the frequency of alcohol intake by black and white students differs significantly over the course of their lives.