Statistical significance explained in plain English

Original source: SimoleonSense.com .

A nice refresher

Via BPS research:

Warren Davies, a positive psychology MSc student at UEL, provides the latest in our ongoing series of guest features for students. Warren has just released a Psychology Study Guide, which covers information on statistics, research methods and study skills for psychology students.

Today I’m delighted to discuss an absolutely fascinating topic in psychology – statistical significance. I know you’re as excited about this as I am!

Why is psychology a science? Why bother with complicated research methods and statistical analyses? The answer is that we want to be as sure as possible that our theories about the mind and behaviour are correct. These theories are important – many decisions in areas like psychotherapy, business and social policy depend on what psychologists say.

Despite the myriad rules and procedures of science, some research findings are pure flukes. Perhaps you’re testing a new drug, and by chance alone, a large number of people spontaneously get better. The better your study is conducted, the lower the chance that your result was a fluke – but still, there is always a certain probability that it was.

Statistical significance testing gives you an idea of what this probability is.

In science we’re always testing hypotheses. We never conduct a study to ’see what happens’, because there’s always at least one way to make any useless set of data look important. We take a risk; we put our idea on the line and expose it to potential refutation. Therefore, all statistical tests in psychology test the possibility that the hypothesis is correct, versus the possibility that it isn’t. The latter possibility is called the null hypothesis.

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