2.7) Inferential Statistics for Psychology Studies

t-test

is used to compare the average scores between two different groups in a study to see if the groups are different from each other. You can use t-tests to compare two groups that occur naturally, such as boys versus girls, or you can compare two groups that you have created in an experiment.

How sure do we need to be before we can decide if a hypothesis is supported?

As a general rule, most psychologists have decided that we should only accept a maximum of a 5% chance that the scores happened at random - in other words, we should be 95% sure that our group differences really aren't due to chance. That means that we want a p-value of between 0% and 5% chance, which would look like a number between 0.00 and 0.05. Any p-value of 0.05 or less means that we can be very sure that our results are valid, and not simply due to chance factors in the study.

Lesson Summary

Inferential statistics are what psychologists use to decide whether hypotheses are supported or not by the results of any study. T-tests compare scores in two different groups, whereas analysis of variance, or ANOVA, tests compare three or more different groups. In order to make sure our results didn't happen due to random chance, we look for a p-value somewhere between 0.00 and 0.05, which tells us that there's less than a 5% chance the results were random. These concepts can help anyone set up a basic psychology study correctly.

p-value.

Whenever we do any statistical test in psychology, including a correlation, a t-test or an ANOVA, the calculation produces a second number, which is the p-value. The p-value tells you the likelihood that the results in the study would have happened simply by random chance.

analysis of variance (ANOVA)

a test that compares the average scores between three or more different groups in a study to see if the groups are different from each other. In other words, an ANOVA is exactly the same as a t-test, but it can analyze multiple groups at once.

Inferential Statistics

ways of analyzing data that allow the researcher to make conclusions about whether a hypothesis was supported by the results. You can remember the term inferential because it comes from the word 'inference,' meaning 'to draw a conclusion from clues in the environment.'