ONEWAY alcohol BY rating /STATISTICS DESCRIPTIVES HOMOGENEITY /PLOT MEANS /MISSING ANALYSIS /POSTHOC=TUKEY ALPHA(0.05). Oneway Notes Output Created 07-JUN-2013 12:39:57 Comments C:\\Users\\donn\\Documents\\GCU Lead fac\\Project with Judy for modifying Data PSY845 to introduce SPSS\\drinks database -revised for course applications DH.sav Input Active Dataset DataSet1 File Label SPSS/PC+ Filter Weight Split File N of Rows in Working Data 35 File Definition of Missing Missing Value Handling User-defined missing values are treated as missing. Statistics for each analysis are based Cases Used on cases with no missing data for any variable in the analysis. ONEWAY alcohol BY rating /STATISTICS DESCRIPTIVES HOMOGENEITY Syntax /PLOT MEANS /MISSING ANALYSIS /POSTHOC=TUKEY ALPHA(0.05). Resources Processor Time 00:00:00.33 Elapsed Time 00:00:00.42 [DataSet1] C:\\Users\\donn\\Documents\\GCU Lead fac\\Project with Judy for modifying PSY845 to introduce SPSS\\drinks database -revised for course applications DH.sav Descriptives Alcohol by Volume (in %) for brand N Mean Std. Deviation Std. Error 95% Confidence Interval for Mean Lower Bound Upper Bound VeryGood 11 4.9000 .17889 .05394 4.7798 5.0202 Good 14 4.6000 .38829 .10377 4.3758 4.8242 Fair 10 4.5100 .34140 .10796 4.2658 4.7542 Total 35 4.6686 .35295 .05966 4.5473 4.7898 Descriptives Alcohol by Volume (in %) for brand Minimum Maximum VeryGood 4.70 5.20 Good 4.00 5.50 Fair 3.90 5.00 Total 3.90 5.50 Test of Homogeneity of Variances Alcohol by Volume (in %) for brand Levene Statistic 1.420 df1 df2 2 Sig. 32 .256 ANOVA Alcohol by Volume (in %) for brand Sum of Squares Between Groups df Mean Square .906 2 .453 Within Groups 3.329 32 .104 Total 4.235 34 F 4.357 Sig. .021 Post Hoc Tests Multiple Comparisons Dependent Variable: Alcohol by Volume (in %) for brand Tukey HSD (I) Rated Quality of Brand (J) Rated Quality of Brand Mean Difference Std. Error Sig. (I-J) Good .12995 .069 .39000 * .14093 .025 VeryGood -.30000 .12995 .069 .09000 .13354 .780 VeryGood -.39000 * .14093 .025 Good Good .30000 Fair VeryGood -.09000 .13354 .780 Fair Fair Multiple Comparisons Dependent Variable: Alcohol by Volume (in %) for brand Tukey HSD (I) Rated Quality of Brand (J) Rated Quality of Brand 95% Confidence Interval Lower Bound Good .0437* .7363 -.6193 .0193 Fair -.2382 .4182 VeryGood * -.7363 -.0437 Good Fair .6193 VeryGood Good -.0193 Fair VeryGood -.4182 .2382 *. The mean difference is significant at the 0.05 level. Homogeneous Subsets Alcohol by Volume (in %) for brand Tukey HSD Upper Bound a,b Rated Quality of Brand N Subset for alpha = 0.05 1 2 Fair 10 4.5100 Good 14 4.6000 VeryGood 11 Sig. 4.6000 4.9000 .784 .082 Means for groups in homogeneous subsets are displayed. a. Uses Harmonic Mean Sample Size = 11.436. b. The group sizes are unequal. The harmonic mean of the group sizes is used. Type I error levels are not guaranteed. Means Plots Need help with answering the following statistic question: Researchers wanted to explore self-esteem in adolescent boys and adolescent girls. Each respondent completed a 10-item self-esteem scale (they chose one rating for each item from a Likert-type scale, 1 = strongly disagree and 5 = strongly agree). The sum of the 10 ratings was each respondent's self-esteem score. Their results were: t = 2.01, d = .90 (40 girls, 40 boys). In an essay of 250-500 words, use the scenario presented in part 1a, above, to thoroughly answer the following questions: 1) What statistical test did the researchers use to determine if there was a statistically significant difference in levels of self-esteem between the boys and the girls? The researcher used independent sample t test for testing the average levels of selfesteem between the boys and the girls. The two samples (adolescent boys and adolescent girls) are independent so t test is the most suitable to test this hypothesis. 2) What was the purpose of calculating a Cohen's d? When is a Cohen's d calculated? Interpret d=.90. What does it mean in this example? Cohen's d is an effect size. The purpose of calculating the effect size is to quantifying the difference between two groups. Cohen's d calculated when we want to measure to size of difference. This can be used when comparing two means. The formula for Cohen's d is simply the difference in the two groups' means divided by the average of their standard deviations. The value of d =0.90, tells us that the two groups' means differ by 0.90 standard deviation. This value of Cohen's d above 0.80 depicts that it is a large effect size. 3) What if the researcher compared the adolescent boys before treatment and again after treating them for depression? What type of t-test would be most appropriate in this case, and why? In this case we have a dependent sample of same adolescent boys before and after the treatment for depression. Whenever the sample is related or dependent, we always use Paired Sample t test. It takes care of the dependencies between the subjects, that is why we are using this test whenever the samples are dependent. Need help with answering the following statistic question: Researchers wanted to explore self-esteem in adolescent boys and adolescent girls. Each respondent completed a 10-item self-esteem scale (they chose one rating for each item from a Likert-type scale, 1 = strongly disagree and 5 = strongly agree). The sum of the 10 ratings was each respondent's self-esteem score. Their results were: t = 2.01, d = .90 (40 girls, 40 boys). In an essay of 250-500 words, use the scenario presented in part 1a, above, to thoroughly answer the following questions: 1) What statistical test did the researchers use to determine if there was a statistically significant difference in levels of self-esteem between the boys and the girls? The researcher used independent sample t test for testing the average levels of selfesteem between the boys and the girls. The two samples (adolescent boys and adolescent girls) are independent so t test is the most suitable to test this hypothesis. 2) What was the purpose of calculating a Cohen's d? When is a Cohen's d calculated? Interpret d=.90. What does it mean in this example? Cohen's d is an effect size. The purpose of calculating the effect size is to quantifying the difference between two groups. Cohen's d calculated when we want to measure to size of difference. This can be used when comparing two means. The formula for Cohen's d is simply the difference in the two groups' means divided by the average of their standard deviations. The value of d =0.90, tells us that the two groups' means differ by 0.90 standard deviation. This value of Cohen's d above 0.80 depicts that it is a large effect size. 3) What if the researcher compared the adolescent boys before treatment and again after treating them for depression? What type of t-test would be most appropriate in this case, and why? In this case we have a dependent sample of same adolescent boys before and after the treatment for depression. Whenever the sample is related or dependent, we always use Paired Sample t test. It takes care of the dependencies between the subjects, that is why we are using this test whenever the samples are dependent