The document discusses correlation in psychological research, focusing on the relationship between two variables without manipulating them. It outlines how correlations can determine if variables are related, using examples and emphasizing the importance of correlation coefficients to measure strength. Additionally, it mentions two main correlation tests: Pearson’s and Spearman’s, used for continuous and ranked data respectively.

1. Correlation recap
Dr David Playfoot
d.r.playfoot@swansea.ac.uk

2. Research questions
• Most psychological research boils down to
two simple questions
1. If I change x does something happen to
y?
2. Are x and y related?
Research questions

3. Correlation
• “Are x and y related?”
1. Do people who spend more time in the
library get better marks?
2. Are intelligence and attractiveness
related?
Correlation

4. Things to remember
• We do not manipulate anything in a
correlational design.
• There is no IV and no DV
• Correlation is usually used when the variables
are continuous, or making distinct groups is
inappropriate.
Correlation

5. Measuring relationships
• In its simplest form:
• Where does this person’s score fall on variable x? Better than
most people? Worse than most people? About average?
• Where does this person’s score fall on variable y? Better than
most people? Worse than most people? About average?
• Compare the two. Do it for lots of people.
Correlation

6. Measuring relationships
If people who are “better than most people” on variable x are
also “better than most people” on variable y
POSITIVE CORRELATION
Correlation

7. Measuring relationships
If people who are “worse than most people” on variable x are
also “worse than most people” on variable y
POSITIVE CORRELATION
Correlation

8. Measuring relationships
If people who are “better than most people” on variable x are
“worse than most people” on variable y
NEGATIVE CORRELATION
Correlation

9. Measuring relationships
If people who are “worse than most people” on variable x are
“better than most people” on variable y
NEGATIVE CORRELATION
Correlation

10. Measuring relationships
• There are two correlation tests we’ll use
• Pearson’s Product Moment
• Spearman’s Rank
Correlation

11. Measuring relationships
• Does the correlation based on z scores per
variable
• i.e. is the score of the participant
above or below the mean for all
participants?
• Says “mean” so must be parametric
Pearson’s

12. Measuring relationships
• Does the correlation based on ranks
• i.e. is the best person at one thing also
the best at another?
• Non-parametric test
Spearman’s

13. THE DIRECTION OF THE CORRELATION IS DETERMINED
BY WHETHER PEOPLE ARE DOING THE SAME THING ON
BOTH VARIABLES, NOT BY WHETHER THEIR SCORES
ARE BETTER/WORSE THAN AVERAGE
Remember

14. Measuring relationships
• We can calculate the degree of correlation
between any two variables as long as they can
be paired.
• Correlation is a only descriptive measure
• Unless we also calculate whether the
relationship is strong enough to be significant
Correlation

15. Measuring relationships
• The strength of a correlation is expressed on a
scale from + 1 through 0 and on to -1.
• This figure is called the correlation coefficient
• The closer to 1, the stronger the relationship
• Ignore the sign when you are assessing the
strength and the significance.
Correlation