Correlations

Question 1

What is a correlation?

Answer 1

-Analysis of the relationship between co-variables
-In correlational research, the variables are not manipulated and instead two co-variables are measured and compared to look for a relationship - one or both co-variables may be pre-existing e.g. school attendance and number of GCSEs achieved
-Each participant has two scores e.g. number of cups of caffeine and number of hours sleep. This is plotted as one point on a scattergraph

Question 2

What is a positive correlation?

Answer 2

One co-variable increases as does the other (but not necessarily at the same rate)
e.g calories consumed and weight gained

Question 3

What is a negative correlation?

Answer 3

One co-variable increases while the other co-variable decreases(but not necessarily at the same rate)
e.g hours spent watching television and level of fitness

Question 4

What is zero correlation?

Answer 4

There is no relationship between the variables
e.g hair color and IQ.

Question 5

What does the correlation co-efficient represent?

Answer 5

-Both the direction and the strength of the relationship between the co-variables, expressed as a value between -1 and +1…

A perfect positive correlation would be expressed as +1
A perfect negative correlation would be expressed as -1
No relationship would be expressed as 0

Both positive and negative coefficient correlations can be described as weak, moderate or strong e.g. a correlation coefficient of 0.03 is a weak positive correlation; a correlation coefficient of - 0.08 is a strong negative correlation

Question 6

What are the strengths of correlational analysis?

Answer 6

-Able to show relationships between variables
-The data may be easily available for researchers to quickly analyse
-Allows predictions to be made when looking at the relationships between co-variables.
-Due to the data being readily available, there are unlikely to be ethical issues.

Question 7

What are the limitations of correlational analysis?

Answer 7

-They do not know causation ie they are unable to show which variable impacts the others.
-Extraneous relationships with other variables may affect the co-variables and the outcome e.g no. of days absence from school may be due illness rather than choice.
-Correlations work well for linear relationships e.g. height and shoe size, but are less successful when dealing with non-linear relationships e.g. number of hours worked and level of happiness