Statistics are a method of summarising and analysing data for the purpose of drawing conclusions about the data.
Carrying out psychological research often involves collecting a lot of data. As psychologists therefore we need to have knowledge of statistics so that we can make conclusions about our data.
We can make a distinction between descriptive and inferential statistics. Descriptive statistics simply offer us a way to describe a summary of our data.
Inferential statistics go a step further and allow us to make a conclusion related to our hypothesis.
Descriptive statistics give us a way to summarise and describe our data but do not allow us to make a conclusion related to our hypothesis.
When carrying out correlational analysis the data is summarised by presenting the data in a scattergram. It is important that the scattergram has a title and both axes are labelled. From the scattergram we may be able to say whether there is a strong positive correlation, a weak positive correlation, no correlation, a weak negative correlation or a strong negative correlation but we can not make a conclusion about the hypothesis.
As the name suggests inferential statistics attempt to make an inference about our data. That is, which hypothesis offers the best explanation for our results.
When we carry out a test of correlation we have two hypotheses. A null hypothesis which states that the results will be due to chance, and the correlational hypothesis, which predicts that there is a correlation or relationship between the two variables
To assess the probability that the results are due to chance an inferential statistical test is used. Inferential statistics tell us whether the relationship between two sets of scores is significant or due to chance. It is an academic convention that in psychology we accept the null hypothesis as the best explanation for out results unless there is a 5% probability (or less) of the results being due to chance.
5% probability is expressed as p<0.05 and if we find that the null hypothesis can be rejected it we can be 95% confident of the conclusions.
When carrying out a test of correlation a Spearman Rho is used.
Using a Spearmanís Rho a value is calculated which is called the observed value. The value then has to be compared with the critical value to determine whether the null hypothesis can be rejected and at what value.