Q1. Suppose the text from a journal article said the following:

...tested for a main effects of treatment (F(2, 97) = 14.77, p < .01, η_P² = .21), education level (F(2, 97) = 1.04, p > .05, η_P² = .01), and a treatment by education interaction (F(2, 97) = 58.13, p < .01, η_P² = .56).

a. What kind of analysis was done?

b. What was found or concluded?

c. How many treatments were there?

d. How many education levels were examined?

Suppose the text from a journal article said the following:

For between subjects effects we found significant education level differences (Wilks' Λ = .384, F (3, 479) = 256.12, p <. 001) and an education by subtest interaction (Wilks' Λ = .951, F (6, 958) = 4.04, p < .001).

Q2. What can you conclude from that? 

Suppose a table from a journal article looks like the one in the separate file accompanying this exam:

Q3. What can you conclude from the information given? 

Q4. A variety of effect sizes have come up in this section.  Some have been new, some old.  They are below.  Tell us when you would use each and what, exactly they are the effect of?

a. Cohen's d

An effect size used to indicate the standardized difference between two means. Used in T-tests, Anova, and meta-analysis.

b. 1 - Λ

c. ω²

Represents a different index of effect size. Similar to N2 but provides a nonbiased estimate of the variance actually accounted for in the population.

d. η^2-     

Presents values of eta squares. Uses the proportion of variance in the criterion variable that is accounted for by the predictor variable. Widely used in Anova with an index of effect size.

e. η_P²

Partial eta squared represents the proportion of variance in the criterion accounted for by a given predictor while excluding the other predictor variables

Q5. What are the differences between an ANOVA and a MANOVA.  Please describe these in terms of:

a. The null hypothesis tested: Anova usually tests a null hypothesis that will have no difference between the means of any of the conditions in the population.  Anova must obtain a F statistic and a corresponding probability value, the null hypothesis is rejected if the p value is below the statistical significance and that means there is a difference in at least two of the conditions. With Manova the conditions are being compared with multiple criterion variables rather than just one like Anova. Manova uses vectors to test null hypothesis. If the P value is lower than the standard criterion the null hypothesis is rejected and it is concluded that there is a difference in at least to of the conditions.

b. The test statistic used to test the null.

Q6. What is the big advantage of using within subjects designs (this includes dependent samples tests)? There are many ways to say this and it is simple (so don't "overthink")?  This is a short answer question - it can be answered in one sentence.

Q7. Below are some possible study scenarios.  What kind of statistical test would you use (at first)?

a. You compare dog owners, cat owners, and petless individuals on a variety of anxiety and depression scores.

b. You compare men and women on mindfulness scores.

c. You compare dog owners, cat owners, and petless individuals on anxiety (only) scores.

d. You compare individuals' anxiety scores before they obtained a pet and after they obtained a pet.

e. You examine the effects of pet ownership (cat, dog, none) and gender (men, women) on anxiety scores.

f. You obtain a significant F test value that compared multiple groups.  What do you do next (in general)?

Q8. What is a sum of squares? There are several, I know; pick one and that one will do. (5 points)

Q9. What is a mean square? There are several, I know; pick one and that one will do.

In terms of Anova a means square is a variance estimate, it estimates the criterion variable's in a sample.

Module Six Objectives

1. Explain t-tests.

2. Explain Oneway ANOVA and when it is used.

3. Explain Factorial ANOVA and when it is used.

4. Explain the F distribution and the F test.

5. Explain MANOVA and when it is used.

6. Explain the steps of MANOVA.

7. Explain the significance tests one (initially) gets when they get a significant MANOVA.

8. Explain the effect size for multivariate tests.

9. Explain what one does next if they get a significant ANOVA or MANOVA

10. Given a table of ANOVA/MANOVA results, interpret and explain the table.

Attachment:- Assignment Files.rar