Martin Dempster

You may be more interested in studying psychology than in crunching numbers, but knowing psychology statistics is essential if you’re going to make all that research data stack up, and have other people understand it. This Cheat Sheet helps you out with some basic concepts in psychology statistics.Determining the role of variables in psychology statisticsIn psychology statistics, research studies which involve collecting quantitative data (any data that can be counted or rendered as numbers) usually require you to collect and store data on a data sheet about several variables.

The measures of dispersion you use in psychology statistics show you the spread or variability of the variable you are measuring. The three main ones are the range, the interquartile range, and the standard deviation. Getting to know the range, interquartile range, and standard deviation The three most important measures of dispersion are defined as follows: The range is the difference between the highest score and the lowest score in a variable.

When putting together the psychology statistics you need to report when you’re describing a variable in a report, you need to know which of the three measures of central tendency – the mode, median and mean – you should use. Be guided by the advantages and disadvantages of each measure. Weighing up the advantages and disadvantages of each measure leads you to the following conclusion: the most appropriate measure of central tendency for a variable depends on the level of measurement of the variable and the nature of the distribution of scores within that variable.

When working with psychology statistics you can classify variables according to their measurement properties. When you record variables on a data sheet, you usually record the values on the variables as numbers, because this makes statistical analysis easier. However, the numbers can have different measurement properties and these determine what types of analyses you can do with these numbers.

In psychology statistics, research studies which involve collecting quantitative data (any data that can be counted or rendered as numbers) usually require you to collect and store data on a data sheet about several variables. When you conduct your statistical analyses on this data, you need to know what role each variable played in your research design.