W7: RQ for Group Differences 2

Question 1

What is dummy coding

Answer 1

Dummy coding transforms a categorical variable with g categories into a meaningful set of g - 1 dummy variables that each have values of either 0 or 1 .

(3 categories = 2 dummy variables with values either 0/1)

Question 2

Rows/Column = Which is dummy?

Answer 2

Row: Factor
Column: Dummy

Question 3

What is investigating mean differences between groups akin to

Answer 3

Akin to a particular form of linear regression

Question 4

What is the “One-Way” design.

Answer 4

One-way because there is only one group classification

Question 5

What is “between-subject” design

Answer 5

Groups are independent.

Question 6

What is null hypothesis in ANOVA. What is it also called

Answer 6

H0: μ1 = μ2 = μ3 / μ1-μ2-μ3=0

Omnibus hypothesis because evidence against it does not tell us which groups differ.

Question 7

Why is a focused investigation better

Answer 7

Often, we are able to propose a priori research questions for the specific ways that differences may occur,

(a) Provides identifiable differences
(b) Can explain everything in the omnibus approach (under certain conditions)

e.g. Is there a difference between students with no experience in maths and those who did VCE
maths among RMHI and ARMP enrolments in 2019?

Question 8

When we have k groups, how many fundamental differences can we find? Why?

Answer 8

contrast variables: k-1

Transitivity

Question 9

What is linear contrast

Answer 9

A set of weights that sum to zero is called a linear contrast.

Net effect: Difference between means of positively-weighted objects and means of negatively-weighted objects.

Question 10

What is a useful property of some contrasts

Answer 10

orthogonality (being uncorrelated).

Question 11

Why is orthogonality a useful property in some contrasts

Answer 11

If a design is balanced and the coefficients in a pair of contrasts are orthogonal, then the mean differences in each contrast do not overlap and do not contain redundancy.

Multipliying them together and then summing the products up = 0 = orthogonal

Question 12

Assumptions for a independent groups. Which is the most important

Answer 12

1. Independence of observations.
2. Normality of observed scores.
3. Homogeneity of group variances (most important)

Question 13

How do we examine “Homogeneity of group variances”.

Answer 13

Levene’s test and/or the Fligner-Killeen test

Question 14

In calculating observed mean difference, what is the decision tree like

Answer 14

1. ) Balance
2. ) Homogeneity
3. ) Normality

Question 15

In calculating standardized mean difference, what is the decision tree like

Answer 15

1. ) Balance
2. ) Normality
3. ) Homoegeneity