Year 12 Psychology: Psychodynamic Approach (AJW)
How science works: Research Methods 2
Correlational Studies
describe ...(ao1)
• A non-experimental design which tests whether there is an association or relationship between two measured variables called co-variables (there is no independent or dependent variable)
• Pairs of scores (quantitative data) are taken from each participant
• The strength and nature (i.e. positive or negative) of any relationship can be seen in the form of a correlation coefficient
• A correlation coefficient is a number between -1 and +1 where ...
o the sign represents whether the relationship is positive (+) or negative (-): this is called the direction of the relationship
o the closer the number is to 1 (+/-), the stronger the relationship: this is called the strength of the relationship
• Negative correlation (-): if one score is high, the other is low
• No correlation: there is no pattern in the data; the variables are uncorrelated
• The hypothesis in a correlational study could be ...
o directional - “there will be” either a positive or a negative correlation
o non-directional – “there will be a significant correlation”
• Just because two variables are correlated this does not mean that one caused the other
• The media and politicians sometimes quote correlational data and imply causation but this is inappropriate, some mother factor may be affecting both variables
| |
|examples... (ao1) |
| |
|Suggest 2 examples of pairs of variables which are likely to show a positive correlation |
|........................................................... and ........................................................... |
|........................................................... and ........................................................... |
| |
|Suggest 2 examples of pairs of variables which are likely to show a negative correlation |
|........................................................... and ........................................................... |
|........................................................... and ........................................................... |
evaluate ...(ao2)
Strengths:
• May be possible to explore unexpected relationships which can later be followed up in a more controlled way
• Same Pps provide both scores and thus the results are not affected by participants variables
Weaknesses:
• Causality cannot be established as there is no attempt made to control confounding variables (thus not scientific)
• Correlational findings may lack credibility if the scores are taken from scales which are not valid and/or reliable
|Task |
|Suggest 1 example of two variables which may be positively correlated and suggest a third variable which may cause the change in the other|
|two, i.e. Variable 1: number of cases of sunburn is likely to be positively correlated with Variable 2: icecream sales on any given |
|summer day but both variables are likely to be determined by variable 3: temperature. |
| |
|Variable 1: ............................................................ may be positively correlated with |
|Variable 2: ............................................ ......................but both variables may be determined by |
|variable 3: ........................................................................... |
Analysing correlational data
• Descriptive statistics help to summarise the data; once pairs of scores have been collected they can be plotted on a scattergraph (AKA scatterplot or scattergram) to see whether they points form a trend.
• It is not necessary to calculate measures of central tendency (averages) or dispersion as these are used when looking for a difference between two conditions or groups;
• a correlation looks for an association or relationship between two scores taken from each person and therefore the averages of each set of scores are not of interest
• it may be possible to draw a line of best fit on the scattergraph and this will suggest the direction and strength of any relationship.
• A Spearmans’s Rho is the appropriate inferential stats test to measure the strength and direction of the relationship; this is because it is
o a test of association
o suitable for ordinal or interval data
• This test will produce an observed value (r) a number between -1 and +1 (the correlation coefficient as described above); this is then compared with the appropriate critical value
• When looking up the critical value, you will need to know
o whether you are doing a one or two tailed test
o the number of participants used
o the chosen level of significance, (usually p ................
................
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