Psychological Report Writing

Through using this website, you have learned about, referred to, and evaluated research studies. These research studies are generally presented to the scientific community as a journal article. Most journal articles follow a standard format. This is similar to the way you may have written up experiments in other sciences.

Primary and Secondary data, including Meta-Analysis

Primary data – information observed or collected directly from first-hand experience. Data that has been collected by the researcher for the study currently being undertaken, specifically relating to the aims and/or hypothesis of the study. Examples of primary data are the results of an experiment, answers from a questionnaire etc.

Measures of Dispersion (Range and Standard Deviation)

In order to summarise a set of scores, a measure of central tendency is important, but on its own it is not enough. A measure of central tendency (such as the mean) doesn’t tell us a great deal about the ‘spread’ of scores in a data set (i.e. is the data made up of numbers that are similar or different?)

Calculating Percentages

Percentages are descriptive statistics that show the rate/number/amount of something within every 100 (per cent). E.g. 5% means 5/100. Percentages can be plotted on a pie chart (whole pie = 100, segments represent a proportion of this 100%).

Sign Test – Inferential Statistics

A non-parametric test used for experiments where the data is at least nominal and repeated measures has been used.

Statistical analysis, like the sign test, produces an observed value, which is compared to a critical value (on a table of values) in order to determine whether a set of results are significant to a specific level.

Statistical (Inferential) Testing

We have all heard the phrase ‘statistical tests’ – for example in a newspaper report that claims ‘statistical tests show that women are better at reading maps than men’. If we wanted to know if women are better at reading maps than men we could not possibly test all the men and all the women in the world, so we just test a small group of men and a small group of women. If we find the sample of women are indeed better with maps than the sample of men, then we infer that the same is true for all men and all women. However, it isn’t quite as simple as that because we can only make such inferences using statistical (or inferential) tests. All statistical tests though are based on the idea of probability. So, before we start to look at the different statistical tests, we need to understand the role that probability plays in statistical testing as no test to guarantee human behaviour 100%.