Statistical Tests Made Simple
Ever wondered how psychologists prove their theories actually work? Statistical tests are your toolkit for making sense of research data, and they fall into two main categories that you'll use constantly.
Tests of difference help you figure out whether groups are actually different from each other (like comparing exam scores between different teaching methods). Tests of correlation show you whether two variables are connected - for instance, whether hours of revision relate to final grades.
The key is matching the right test to your data type and research design. Once you understand the basic pattern, choosing becomes straightforward.
Quick Tip: Think of statistical tests like recipes - you need the right ingredients (data type) and method (test design) to get the perfect result!
Your data comes in three main flavours, each requiring different statistical approaches. Nominal data is purely categorical - like favourite subjects or eye colour. You can't order these meaningfully, so they need special tests.
Ordinal data can be ranked but the gaps between ranks aren't equal - think satisfaction ratings from 1-10. Finally, interval data uses proper numerical scales with equal gaps between values, like reaction times or test scores measured in seconds or percentages.