Module 4: Multiple Levels of IVs

Question 1

What is a single-factor experiment?

Answer 1

An experiment with one independent variable with multiple conditions/levels
Also known as a one-way ANOVA

Question 2

What is a two-factor experiment?

Answer 2

An experiment with two independent variables with multiple conditions/levels
Also known as a two-way ANOVA

Question 3

State the null hypothesis of a one-way ANOVA

Answer 3

All mean levels of the independent variable are equal H0:µ1=µ2=µ3=µ3

Question 4

State the alternative hypothesis of a one-way ANOVA

Answer 4

At least one mean level is different from the others

Question 5

For the t-test calculations, the means are inputted into the calculation whereas in the ANOVA calculation, means are not inputted ____________ are instead

Answer 5

Variances

Question 6

In ANOVA we assess….

Answer 6

The amount of variability and explain source of the variability

Question 7

If we compare a single score drawn from each of two conditions (between treatments variability) the two scores may vary due to… (3 reasons)

Answer 7

1. Treatment effect
2. Individual differences
3. Experimental error

Question 8

If we compare two scores drawn from the same condition (within treatments variability) the scores may vary due to… (2 reasons)

Answer 8

1. Individual differences

2. Experimental error

Question 9

Why do we not need to worry about treatment effects in within treatment designs?

Answer 9

Treatment effect is a constant within conditions

Question 10

Conceptually the F ratio is defined as…

Answer 10

The ratio of the variance in the scores

f = between subjects variability / within subjects variability

Question 11

Factors that influence F ratio to be larger?

Answer 11

• Large treatment effect

- Small values for individual differences and experimental error

Question 12

Denominator of the F-test

Answer 12

Measures unsystematic variability in scores (i.e., individual differences and experimental error)

Question 13

Numerator of the F-test

Answer 13

Measures same unsystematic variability in scores AND systematic variability (i.e., treatment effects)

Question 14

If the null hypothesis is true…

Answer 14

The variance associated with treatment effects should be zero or nearly equal to 1

Question 15

If the null is false…

Answer 15

The variance associated with treatment effects should be larger than 1

Question 16

Analysis of variability involves two parts:

Answer 16

1. Analysis of sums of squares (SS)

2. Analysis of degrees of freedom (df)

Question 17

A posteriori tests aka post hoc tests

Answer 17

Follow-up tests that are not based on prior planning or clear hypotheses
Only considered when the F-test is significance

Question 18

A priori tests aka planned tests

Answer 18

Planned or theoretically driven follow-up tests

Question 19

Family-wise error

Answer 19

Cumulative likelihood of making a type I error

Post hoc tests control for this error

Question 20

The more post hoc tests hold down the family-wise error, the more ____ also goes down

Answer 20

Power (likelihood of making a type II error increases)

Question 21

Least Significant Difference (LSD)

Answer 21

Common post hoc test

Does not control for family-wise error

Question 22

Planned contrast

Answer 22

Specifying a very specific comparison based on research question

Question 23

In a planned contrast, comparisons are specified by the _________ ___________

Answer 23

Contrast weights

Question 24

Contrast weights must sum to…

Answer 24

Zero

Question 25

Non-orthogonal contrasts

Answer 25

Results of contrasts overlap and are NOT independent of one another

Question 26

Orthogonal contrasts

Answer 26

The results of one contrast are completely independent of the other

Question 27

Bonferroni adjustment

Answer 27

Not necessarily a post hoc test, rather an adjustment to alpha depending on number of comparisons

Alpha / number of comparisons

Going beyond 3 or 4 comparisons will make power very poor

Question 28

Tukey’s HSD

Answer 28

Common post-hoc test

Tests all pairwise comparisons while controlling for family-wise error

Good when testing lots of comparisons