1. 1.1 Research Methods and techniques
Correlation

2. The relationship between two variables

3. Correlation The relationship between two variables For example:
Hand span + intelligence
Stress at work + number of sick days
School absences + final grades
Correlation = association
Correlation does not = cause-and-effect relationship

4. When would you use a correlation?
When you want to look at naturally occurring variables
Complete the following on your A3

5. What do we think happens?
As the temperature increases
So too does ice-cream sales
This is called a POSITIVE correlation
As one variable increases, so too does another
A scatter graph is used to show how one variable is affected by another variable

6. What about… As number of days absent from school increases…
What will happen to students grades?
Students grades decrease
This would be a NEGATIVE correlation
As one variable increases, another decreases
What about…

7. What about… Likelihood of owning a cat and being struck by lightening?
There is no relationship between these variables
This is called NO correlation

8. Complete handout 1

9. Is there a correlation between stress & absence?
Participant
Stress (rating110)
absences (days) 1 2 4 6 3 10 29 7 5 8 15
Plot a scattergram on your white board to see the correlation.

10. Correlation Coefficient
Measures the strength of a correlation
= Correlation co efficient (from +1 to -1).
perfect / strong / moderate / weak / no / weak / moderate / strong / perfect
relationship
Nearer to +1/-1 = perfect

11. Positive correlation (+1) / (increases)
Negative correlation (-1) \ (decreases)

12. Interpret the following correlation coefficients
0.87
0.65
1.6
–0.23
0.009
–0.76
–23.9
1.00 / \

13. What do you think these show? Strong/weak Positive/negative

14. Evaluating correlation
Measuring the strength of relationships – precise quantitative measure
Allows experimenters analyse statistically where it might be unethical
Identifies relationships opening up new lines of experimental research
Further research may indicate probability of relationship being causal
Impossible to establish cause and effect
Cannot take outside variables into account (the 3rd factor might be causing it).

15. One last thing…
Can have linear correlations OR Curvilinear correlations =
= straight lines curved, but still a predictable relationship Eg heat levels and aggression levels

16. Homework for the October break
Complete any gaps in your folder
Complete the self-report booklet
Update your key terms booklet
RM Workbook page 21
Complete correlation workpack