Flashcards in Stats Deck (24):

1

## Give 2 conditions for using factorial designs.

### More than 1 IV is thought to effect a DV and/or ignoring an IV detracts from the explanatory power of our experiments.

2

## Give 2 limits of between-subjects designs.

### Participant variables and number of participants required.

3

## Give 2 limits of within-subjects designs.

### Practice effects and long testing sessions.

4

## What are the assumptions in mixed factorial ANOVA?

### Interval/ratio data, normal distribution, homogeneity of variance (between-subjects) and sphericity of covariance (within-subjects).

5

## What should you do if the assumptions of mixed factorial ANOVA are violated?

### Process with caution, report the violation, and use corrected results if possible.

6

## If there are interactions in a mixed factorial ANOVA, which formulae do you use?

### Within-subjects formulae.

7

## What are the assumptions for Pearson’s correlation?

### Linear variable relationship, interval/ratio data and normal distraction free of outliers.

8

## What are the assumptions for Spearman’s correlation?

### Monotomic variable relationship and ordinal/interval/ratio data.

9

## Why do distribution and outliers not influence Spearman’s correlation?

### They use ranks, not means and SDs.

10

## How are degrees of freedom calculated in a Pearson’s correlation?

### df - n*pairs - 2

11

## Give 2 factors that affect the significance threshold of a correlation coefficient.

### The magnitude of the correlation and the number of observations.

12

## When are tests of regression used?

### When causal relationships between variables are likely.

13

## What type of tests are regression?

### Inferential statistical tests of association.

14

## What are the assumptions of regression?

### Linearity, interval/ratio data, normal distribution free of outliers and homoscedasticity.

15

## Describe residuals.

### The distance between the actual outcome and predicted outcome.

16

## What do you do if there is heteroscedasticity in a regression?

### Proceed with caution and inform the reader.

17

## What is multicollinearity and how do you test for it?

### When predicted variables are highly correlated, tested by running simple correlations.

18

## How much should variables correlate to be considered to have multicollinearity?

### (+/-) 0.8

19

## What do mixed factorial designs use very efficiently?

### Participant numbers and participant time.

20

## What is homoscedasticity?

### When residuals have the same degree of variation across all predictor variable scores.

21

## What is multiple regression?

### Predicting one outcome variable from more than one predictor variable.

22

## Describe simultaneous regression.

### All predictors are entered at the same time - used for explanatory analysis.

23

## Describe hierarchical regression.

### Predictors are entered in a pre-defined order - used when informed by theory.

24