Correlation

Question 1

What are three characteristics of relationships?

Answer 1

1. Direction (positive vs. negative)
2. Strength of association (strong vs. weak; perfect vs. imperfect)
3. Form (linear vs. non-linear)

Question 2

How can relationship direction and strength of association vary?

Answer 2

positive vs. negative
strong vs. weak; perfect vs. imperfect

Question 3

How can relationship form vary?

Answer 3

linear: positive or negative
vs.
non-linear: independent or curvilinear

Question 4

Correlation coefficient

Answer 4

expresses the strength and direction of a relationship
- perfect negative relationship: -1
- perfect positive relationship: 1
- no relationship (variables are independent): 0

Question 5

Pearson r

Answer 5

a type of correlationship coefficient used to describe LINEAR relationships; a measure of the extent to which paired scores occupy the same or opposite positions within their own distributions

• leading zeros (before the decimal point) are not used when reporting
• a non-linear relationship may have a Pearson r value of 0, but this doesn’t mean there is no relationship (just no linear relationship)

Question 6

Line of best fit

Answer 6

straight line in a scatterplot drawn so that number of points above and below the line is about equal

• outliers can have a large effect

Question 7

What should you do before calculating correlation coefficients?

Answer 7

• create a scatterplot
• look for outliers
• check for linearity
• consider whether the ranges of the two variables are sufficient to show their true relationship

Question 8

Range restriction

Answer 8

the limitation of the full range of the total possible scores to only a narrow portion of that total

via:
- sampling
- measurement procedures
- other aspects of experimental design

Question 9

How do you calculate Pearson r?

Answer 9

• convert to z-scores to put variables on the same scale
• calculate X2, Y2, and XY for all raw values
• calculate the sum for all columns
  (Subject X Y X2 Y2 XY)

Question 10

How do you interpret Pearson r?

Answer 10