Correlations

What is the difference between correlations and experiments?

Experimental designs require manipulation of the IV and a measurement of the resulting change in the DV. In a correlational study, no variables are manipulated, two co-variables are measured and compared to look for a relationship

What are co-variables?

The two factors/variables that are measured/collected by the researcher and then compared to each other

What are some examples of co-variables?

• Age

• IQ

• Reaction time

• Bank account balance

• Number of pets

• Height

• Hostility level

What is a scattergram?

A graph used to plot the measurements of two co-variables. Scattergrams visually display the relationship between co-variables

What is a positive correlation?

As one co-variable increases the other co-variable increases

What is a negative correlation?

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

What is zero correlation?

There is no relationship between the values of the two co-variables

Analysis of the relationship between co-variables:

The strength and direction of a correlation can be described visually with a scattergram, or numerically with a correlation coefficient

What is a correlation coefficient?

Represents both the strength and direction of the relationship between the co-variables as a number between -1 and +1

How are correlation coefficients calculated?

Using statistical tests such as Spearman’s rho or Pearson’s r. Inter-rater and test-retest reliability is assessed in this way. A correlation coefficient equal to or greater than 0.8 is usually judged to show a strong correlation

AO3 - Limitations

• Correlation does not show causation. While a strong correlation may suggest a relationship exists between two variables, it does not show which co-variable led to the change in the other co-variable and there is the possibility that an unknown third variable caused the change in both covariables

AO3 - Strengths

• Correlational studies can highlight potential causal relationships, these can then be tested with experimental methods to discover cause and effect relationships

• Often the co-variable data already exists and is easily accessible, this means there is usually few ethical problems in data collection

• Correlation coefficient is a useful tool in describing both the direction and strength of relationships between factors