1. In other words the relationship between variables

2.  Offer us a way of establishing whether there is a relationship between two variables  enable us to assess the strength of that relationship by calculating a correlation coefficient (R) correlation coefficient (R) The statistical test is known as the Spearman’s Rho  Unlike experiments, correlational studies do not tell us about causal (cause and effect) relationships

3.  The difference between an experiment and a correlation is  An experiment looks at cause and effect relationship  a correlation looks at the relationship between 2 variables- it doesn’t look at which variable has caused the other variable to change.

4.  If the 2 variables were stress and hours of sleep:  An experiment would have 2 conditions:-  IV  IV - 1 group might be given a non-stressful task before sleeping. The 2 nd group might be given a stressful task before sleeping.  DV  DV - Amount of hours of sleep would be recorded in both conditions. We assume the IV has an effect on the DV

5.  A correlation might investigate self-reported levels of stress and the number of hours sleep a participant had. manipulated,  The difference is that in an experiment something is manipulated, where as correlations are merely looking at 2 variables occurring at the same time. IVDV Therefore there is no IV or DV in a correlation.

6.  You have to look at the two variables to see if they are occurring at the same time.  The 2 variables have to be measurable Question: On your white boards write down the term for making something measurable or idiot proof ? operationalisation. answer operationalisation.

7.  Number of subjects taken at 6 th form and hours of homework  Self-reported stress levels and personality type  Out of school activities and grades  Hours of TV watch and level of aggression

8. CCan you come up with 3 ideas for a correlation? WWWWrite them on your white board now

9.  There are 3 types of correlations positive and negative and zero 0   Positive-as one variable increases the other variable increases.  Negative- as one variable increases the other variable decreases.

10.  The results from a correlation can be plotted on a scattergram. The scattergram will show whether there is a positive correlation, a negative correlation, or no correlation at all  You can analyse the relationship by  1. Drawing a scattergram  2. Calculating a correlation coefficient (R)

11. This is a positive correlation because as the number of hours watching TV increases so does the level of aggression. Line of best fit

12. This is a negative correlation because as the temperature increases, the number of clothes worn decreases.

13. This scattergram shows there is no correlation between head circumference & IQ. zero This is also known as a zero correlation

14.  Gives us a statistical method for assessing the strength of a correlation  The sign (+ or -) tells you the direction of the correlation  The number (between 0 and 1) tells you the strength of the correlation -1  A perfect negative correlation would be -1

15. What kind of correlation is this – write it on your whiteboards

16.  Well done if you got this right WWhat number would represent this perfect positive correlation?

17. As one variable rises, the other falls

18.  Well done if you got this right

19. infer What can we infer from this scattergram? White board time again

20. AA correlation between two variables does not mean that changes in one variable is causing changes in the other IIt simply means there is a relationship between the two variables that might be worth investigating further What number would represent no correlation at all?

21. Advantages Advantages Disadvantages Disadvantages  Data may have already been collected Other factors which are ignored- not controlled for Ideal for showing a link between 2 measures No cause and effect Provides quantitative dataSome problems of using a scale Can use observational data and self-report measures= high ecological validity. As some results are taken from a laboratory environment the results may have low ecological validity.

22. RResearch question: is there a relationship between stress and illness? VVariable 1: scores on a stress questionnaire VVariable 2: number of days absent from college since September HHypothesis: There will be a positive correlation between stress scores and number of absences WWrite the null hypothesis on your whiteboard now

23.  Research question: is there a relationship between absence from college and final AS marks?  Variable 1: absences  Variable 2: final AS mark (Max 300)  Null Hypothesis: There will be no correlation between absences and AS marks  Write the alternate hypothesis now

25. To design your own correlational study you will need To write a testable hypothesis and a null hypothesis To decide how you will measure your 2 variables. To know what your sample will be To know how you will carry out your research