PLEASE HELP! We are working on comparing t statistics/tests for comparing two sa

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PLEASE HELP! We are working on comparing t statistics/tests for comparing two samples for both repeated and independent samples, and something about ANOVA I just need to know which test to solve for each of these so I can start the calculations....

You work in student affairs at a university. You want to assess the effectiveness of two programs designed to support students who have been identified as being at risk of not graduating. The first program is the Academic Success Program. In this program, a full-time staff member teaches students study skills in a class setting, then meets with each student once per week to help them develop and follow an individualized study plan. In the second program, trained peer mentors meet with students weekly to study together and provide social support Peer mentors also refer students to resources such as the counseling center, student health and wellness, the disability resource center, and other services on campus. To measure the effectiveness of these programs, you have each student complete the College Student Success Scale (CS, which measures many factors that predict the likelihood of graduation. To control for any pre-existing differences among your groups, you have them complete the scale the first week of their freshmen year, and again at the end of their freshman year. In addition, you also have them complete the Belonging On Campus Scale (BOC) one time at the end of their Freshman year to assess their sense of belonging at your university. Their scores are listed below. Higher scores on the BOC indicate a greater sense of belonging at the university. Higher scores on the CSS reflect greater chance of success, thus each program has worked if CSS scores have increased significantly Group 1: Academic Success Program only Group 2: Peer mentor program only Group 3: Both programs Group 4: Student chose not to participate in any program

Explanation / Answer

To answer the question ,we need ot know about the nature of variables.

There are few observations.

1. Sample size is very small (10).

2. Sample data is both depenendent and indepenendent.

In order to choose right kind of statistic ,we make use of the following refernce.

Now we can make use of the table above to determine the statistic to be employed.

For first question , we are required to compare the means before and after for a particular given group. .Clearly it consists of one IV with two levels (before and after) .The appropiate test should be paired t test.

In second question ,there is one level (after) for four different groups .This will be done via factorial ANOVA.

In third question again there are two independent variables on one level (after) ,Hence go for ANOVA.

Number of Dependent Variables Nature of Independent Variables Nature of Dependent Variable(s) Test(s) 1 0 IVs (1 population) interval & normal one-sample t-test ordinal or interval one-sample median categorical (2 categories) binomial test categorical Chi-square goodness-of-fit 1 IV with 2 levels (independent groups) interval & normal 2 independent sample t-test ordinal or interval Wilcoxon-Mann Whitney test categorical Chi-square test Fisher’s exact test 1 IV with 2 or more levels (independent groups) interval & normal one-way ANOVA ordinal or interval Kruskal Wallis categorical Chi-square test 1 IV with 2 levels (dependent/matched groups) interval & normal paired t-test ordinal or interval Wilcoxon signed ranks test categorical McNemar 1 IV with 2 or more levels (dependent/matched groups) interval & normal one-way repeated measures ANOVA ordinal or interval Friedman test categorical repeated measures logistic regression 2 or more IVs (independent groups) interval & normal factorial ANOVA ordinal or interval ordered logistic regression categorical factorial logistic regression 1 interval IV interval & normal correlation interval & normal simple linear regression ordinal or interval non-parametric correlation categorical simple logistic regression 1 or more interval IVs and/or 1 or more categorical IVs interval & normal multiple regression analysis of covariance categorical multiple logistic regression discriminant analysis 2+ 1 IV with 2 or more levels (independent groups) interval & normal one-way MANOVA 2+ interval & normal multivariate multiple linear regression 0 interval & normal factor analysis 2 sets of 2+ 0 interval & normal canonical correlation

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