Correlations

Question 1

Association

Answer 1

Illustrates the strength and direction of an association between two co-variables

Question 2

Scattergram

Answer 2

Correlations are plotted on a Scattergram. One co-variable is on the x-axis and the other is on the y-axis

Question 3

Positive Correlation

Answer 3

Co-variables rise or fall together

Question 4

Negative Correlation

Answer 4

One co-variable rises and the other falls

Question 5

Zero Correlation

Answer 5

No relationship between the two co-variables

Question 6

Describe experiments and their difference to correlations

Answer 6

In an experiment:

• the researcher manipulates the IV and records the effect on the DV.
• in a correlation there’s no manipulation of variables and so cause and effect cannot be demonstrated

Question 7

Describe correlations and use of EV’s

Answer 7

In a correlation:

• the influence of EV’s is not controlled
• so it may be that a third untested variable is causing the relationship between the co-variables
• this is called an intervening variable

Question 8

Two Strengths of Correlations

Answer 8

+ Useful starting point for research. By assessing the strength and direction of a relationship, correlations provide a precise measure of how two variables are related. If variables are strongly related it may suggest hypotheses for future research.

+ Relatively economical. Unlike a lab study, there is no need for a controlled environment and no manipulation of variables is required. Correlations are less time-consuming than experiments

Question 9

Two Limitations of Correlations

Answer 9

• No cause and effect. Correlations are often presented as causal (eg by media) when they only show how two variables are related. There may be intervening variables that explain the relationship.
• Method used to measure variables may be flawed. For example, the method used to work out an aggression score might be low in reliability (observational categories might have been used)