A Level Psychology at Spalding Grammar School

In research, we often want to find out if there is a relationship between two or more variables, eg. is there a relationship between hard work and exam results?  A positive correlation means that high values of one variable are associated with high values of the other variable, eg. the more hours of work student put into revision, the higher their exam score.  A negative correlation means that high values of one variable are associated with low values of another variable, eg. the more hours spent in the pub, the lower the exam results.  If there is no relationship, the variables are said to be uncorrelated.

A common mistake is to assume that when there is a strong connection between two variables, one must be causing the other to happen.  Correlation does not prove causation.  This mistake is often made by the media, politicians, etc. who make comments about the links between unemployment and crime or certain tastes in music and drug abuse.  The correlations may exist, but they do not prove any causal relationship.

• Does unemployment cause crime?
• Does crime cause unemployment?
• Or does some third factor (poverty? poor education? discrimination?) cause both?

Consider: there is a proven correlation between church attendance in a neighbourhood and crime rates in that area.  How can this be explained?

Among the core studies, Maguire uses the correlational method when looking at the brains of London taxi drivers. She found that, the longer they had been taxi drivers, the greaterthe alteration in the parts of their brains responsible for navigation and memory.

Strengths of correlational research	Limitations of correlational research
Researcher can measure relationships between naturally occurring variables without manipulating or controlling them Correlations can predict the value of one variable when we only have information about the other one	Does not produce conclusions about cause and effect – some other factor may be responsible Some relationships between two variables do not show up as correlations

Now download this slideshow about the different types of self-reports used in Psychology.

• This lecture handout might help you take notes.
• This handout explains the different types of correlational relationships

You are going to be collecting data from two independent measures and plotting a scattergram to see if there is a relationship between these measures. Some suggestions include:

• Shoe size and IQ
• Hours of sleep and alertness
• Size of breakfast and happiness
• Attitude to subject and success in subject
• Hours spent watching TV and memory recall

Hypothesis

When you are looking for a correlation between two variables, you are looking for a relationship.  Words like “difference” and “effect” should not appear in a correlational hypothesis.  You should predict the direction of the relationship you are looking for:

1. A positive correlation means that as one variable increases, so does the other
2. A negative correlation means that as one variable increases, the other decreases (and vice versa)

A correlational hypothis will look like this:

There will be a correlation [say whether positive or negative] between variable X and variable Y

Measuring Correlations

You will need to draw a SCATTERGRAM to show your data.  This is where you have one variable plotted on each axis and points on the scattergram represent each participant’s score on both variables.

• If all the points are around a line moving from the bottom left to the top right of the graph, this suggests a positive correlation between the variables.
• If the pattern is from top left to bottom right, this suggests a negative correlation

Are the following correlations positive or negative?

1. The hotter the weather, the higher the ice cream sales
2. The smaller the miniature pony, the more valuable it is
3. The more overcrowded the tower block, the more vandalism reported
4. The lower the calorie consumption, the less the weight
5. The lower the food prices, the more business done by the supermarket

Correlations can be expressed as a CORRELATIONAL COEFFICIENT.  This is a number between +1.0 (perfect positive correlation) and –1.0 (perfect negative correlation).  A correlation of +0.6 would be a fairly strong positive correlation; a correlation of –0.9 would be an even stronger negative correlation.  A coefficient of 0 indicates no correlation. Correlational Coefficients can be worked out mathematically using a simple formula, but quite a few websites and computer spreadsheet programs will do it for you.

Assertiveness and watching TV

Aim:To see whether watching TV is related to assertiveness (because many programs encourage such behaviour)

Method: You need to obtain two pieces of data from everyone in your class.

1. The number of hours they watched TV in the last 24 hours (presuming the more TV watched, the more “assertive” programmes were watched).
2. An “assertiveness” score each person should rate themselves (or be rated by someone else) on a scale of 1 to 10 where 10 is very assertive.

Results: Put the scores for each person on a scatter graph. Calculate a correlation coefficient to assess the strength of the correlation. Use the Excel method described below

Excel: Open a new document (select file new blank workbook). Select insert chart XY scatter and press next. Place the cursor at the very top left of the page, click and drag across 2 rows and then down 16 rows. Press next next finish. Now enter your pairs of scores. Do not enter data into the top row. To calculate correlation coefficient, place the cursor in an empty box. Select insert function. In the top box type “correl” and press go and then OK. Screen now says “array 1”and “array 2”. Click in array1 and then move the cursor to the top of the first column. Do the same for array2. Try changing some of the numbers and see how this alters your scattergraph and the correlation coefficient.

• This Correlations Proforma will help you organise your notes.
• This Evaluation Proforma will help you focus on the strengths and weaknesses of your research.
• This Excel Document has a sample scattergram already on it. Try changing the scores to see the scattergram change shape...