lecture notes Flashcards

1
Q

continuous data

A

ANOVA

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

What type of inferential test analyzes the magnitude of difference between two means?

a) ANOVA
b) chis-square
c) ttest
d) factorial AONVA

A

C

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

another word for row means and column means

A

marginal means

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

Marginal means

A

the main effects of each factor (IV)

-seen in row and column totals

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

interaction means

A

cell data

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

What are the benefits of factorial ANOVA

A
  1. allows us to capture more complexity
  2. helpful in studying social and psychological phenomena b/c they are affected by more than one IV
  3. allows us to examine the interactions of variables
  4. it is economical- we can test multiple hypotheses simultaneously
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

omnibus test

A

Omnibus tests are statistical tests that are designed to detect any of a broad range of departures from a specific null hypothesis

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

partitioning variance in factorial ANOVA

A

SSgroups are partitioned even further than one way ANOVA- SSa, SSb, SSab (variance of each factor and then variance of interaction of factors)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

the higher your f…

A

the smaller and more significant your p will be

factorial ANOVA

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

when your main effects and interaction effects are both significant which one do you interpret first?

A

YOUR INTERACTION

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

An interaction occurs when…

A

the effects of one IV depend on the level of the other IV

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

Tools to understand interaction effects

A
  1. cell mean plots (visual pattern of interaction, ordinal/disordinal)
  2. simple effects analysis (to determine the source of our significance- one way ANOVA)
  3. Tukey HSD test (all possible pairs of cell means are tested)
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

When do you use Tukey over simple effects analysis?

A

Simple effects analysis would be suitable when there are only two levels to each of the simple effects (if there were more than two levels then Tukey’s HSD would be preferable

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

ordinal interaction

A

have simple effects that are in the same direction

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

disordinal interaction

A

have simple effects that are in opposite directions

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

parallel lines

A

there is no interaction

17
Q

when have disordinal interactions

A

you must be particularly careful when interpreting your main effects

18
Q

what type of data do ttests use?

A

continuous data

19
Q

which type of ANOVA has less error?

A

Factorial - because you explain a lot more of the variance