13. Assessing Relationships 1

Question 1

correlation

Answer 1

• measure of relationship between variables

- whether it’s significant

Question 2

correlation and causality

Answer 2

can’t infer causality, just that a relationship exists

Question 3

What 3 ways can variables be related?

Answer 3

• positively
• negatively
• not related

Question 4

When must you assess scatterplots?

Answer 4

before running a correlational analysis

Question 5

covariance

Answer 5

assess whether or not the 2 variables covary

Question 6

two types of covariance

Answer 6

• positive

- negative

Question 7

positive covariance

Answer 7

as one variable deviates from the mean, the other deviates in the same direction

Question 8

negative covariance

Answer 8

as one variable deviates from the mean, the other deviates in the opposite direction

Question 9

standardized measure of covariance

Answer 9

correlation coefficient

Question 10

most common correlation coefficient

Answer 10

Pearson correlation coefficient (Pearson’s r)

Question 11

Pearson’s r: value must be between

Answer 11

-1 and 1

Question 12

Pearson’s r: +1 means

Answer 12

positive correlation

Question 13

Pearson’s r: -1 means

Answer 13

negative correlation

Question 14

Pearson’s r: 0

Answer 14

no relationship

Question 15

effect sizes: Pearson’s r

Answer 15

small: +/- .1
medium: +/- .3
large: +/- .5

Question 16

assumptions of Pearson’s r

Answer 16

• interval level

- if you want to determine whether it’s significant, must be normally distributed

Question 17

Other than Pearson’s r, what else is used?

Answer 17

• Spearman’s correlation coefficient

- Kendall’s tau correlation coefficient

Question 18

What are Spearman’s and Kendall’s tau used for?

Answer 18

nonparametric data

• not normally distributed
• interval level