Correlations

Question 1

Correlation

Answer 1

Illustrates the strength and direction of an association between two or more co-variables (things that are being measured). Plotted on scattergram.

Question 2

Positive and negative correlation

Answer 2

Positive -As one co-variable increases so does the other

Negative-As one co-variable increases the other decreases.

Question 3

Difference between correlations and experiments

Answer 3

In an experiment the researcher controls or manipulates the IV in order to measure the effect on the dependant variable.

In contrast in correlation there is no manipulation of one variable and therefore it is not possible to establish cause and effect between one co-variable and another. Even if we found a strong positive correlation between caffeine and anxiety level we cannot assume that caffeine was the cause of the anxiety.

Question 4

Strengths of correlation

Answer 4

Useful preliminary tool for research. Provide a precise and quantifiable measure of how two variables are related. This may suggest ideas for possible future research if variables are strongly related or demonstrate an interesting pattern. Often used as a starting point to assess possible patterns between variables before researchers commit to an experimental study.

Relatively quick and economical to carry out. No need for a controlled environment and no manipulation of variables is required. Data collected by others (secondary data such as government statistics) can be used, which means correlations are less time-consuming than experiments.

Question 5

Limitations of correlation

Answer 5

Lack of experimental manipulation and control within a correlation, studies can only tell us how variables are related but not why. Can’t demonstrate cause and effect. Don’t know which co-variable is causing the change.

Another untested variable may be causing the relationship between the two co-variables-intervening variable (third variable problem). Eg people who have high pressure jobs spend a lot of time feeling anxious and drink a lot of caffeine because they work long hours.

Can be misused or misinterpreted. Relationships between variables are sometimes presented between variables as causal when they aren’t- especially by media.