Correlational studies

Question 1

Continuous variable

Answer 1

A variable that can take on any value within a certain range.
For example:
Liking for football on a scale of 1-10 is continuous whereas the football team a person supports isn’t.

Question 2

Intervening variable

Answer 2

A variable that comes between two other variables, which is used to explain the association between those two variables.
For example:
If a positive correlation is found between ice cream sales and violence this may be explained by an intervening variable - heat - which causes the increase in ice cream sales and the increase in violence.

Question 3

Correlation

Answer 3

Determining the extent of an association between two variables.
The co-variables may not be linked at all - zero correlation.
They may both increase together - positive correlation.
As one co-variable increases, the other decreases - negative correlation.

Question 4

Correlation coefficient

Answer 4

A number between -1 and +1 that tells us how closely the co-variables in a correlational analysis are associated.

Question 5

Linear correlation

Answer 5

A systematic relationship between co-variables that is defined by a straight line.

Question 6

Curvilinear correlation

Answer 6

A non-linear relationship between co-variables.

Question 7

Scatter diagram

Answer 7

A graphical representation of the association between two sets of scores.

Question 8

Significance

Answer 8

A statistical term indication that the research findings are sufficiently strong for us to accept the research hypothesis under test.

Question 9

Difference between experiments and correlations

Answer 9

In an experiment the investigator deliberately changes the independent variable in order to observe the effect on the dependent variable.
Without this deliberate change no casual conclusions can be drawn.
In a correlation the variables are simply measured - no deliberate change is made.
Therefore, no conclusion can be made about one co-variable causing the other.

Question 10

Correlations - advantages

Answer 10

Correlations have their own special value.
They’re used to investigate trends in data.
If a correlation is significant then further investigation is justified.
If a correlation is not significant then you can rule out a casual relationship.
As with experiments, the procedures in a correlation can usually be easily repeated again.
This means that the findings can be confirmed.

Question 11

Correlations - disadvantages

Answer 11

People jump to casual conclusions.
This a problem because such misinterpretation of correlations may mean that people design programmes for improvement based on false premises.
As with experiments, a correlation may also lack internal / external validity.