Measures of Central Tendency and Dispersion

Ever wondered how psychologists make sense of all their research data? Measures of central tendency tell us what's "typical" in a dataset, whilst measures of dispersion show us how spread out the data is.

The mean is your classic average - add everything up and divide by how many values you have. It's brilliant because it uses every single score, but one massive outlier can completely skew your results. Think about how one billionaire in a room of students would make the "average" income completely unrealistic!

The median is the middle value when you line everything up in order. It's much better at ignoring those pesky extreme scores, but it completely ignores the actual values of most of your data. The mode is simply the most common value, which works perfectly for categories like favourite colours, but can be pretty useless when you've got loads of different modes.

For measuring spread, range is dead simple - just subtract the lowest from the highest value. However, it tells you nothing about whether your data clusters around the middle or spreads evenly. Standard deviation is far more sophisticated, showing the average distance from the mean, though extreme values can still mess with it.

Key Tip: Choose your measure based on your data type and whether you've got extreme outliers lurking about!