OK, you’ve run the analysis of variance and the F-test is significant. So you know your groups aren’t all the same. But you don’t want … Read More

It is not necessary that you eyeball all of the individual data points to decide whether or not your groups differ. Most analysts gets stuck … Read More

Does the average difference between groups matter? Or was it simply random noise? With one-way ANOVA, you can find out. This compares all the groups … Read More

Alright, so you’ve done it. You collected data, ran the same subject through three different conditions. You probably measured their reaction time before, during, and … Read More

A balanced two-factor analysis of variance lets you test two factors together. In other words: Does your new fertilizer increase yield, and is that good … Read More

One way ANOVA exist to solve your multiple comparisons problem by considering all groups simultaneously. The difference between group isn’t really what it’s measuring; it’s … Read More

Is there a relationship between two things? That’s the basic question you begin with. Did a medical treatment improve outcomes? Was a marketing email responsible … Read More

Look at the contingency table. You observe that more people in treatment group have recovered than in control group. Your intuition tell you this means … Read More

With the chi-square test of independence, for example, you can tell whether your marketing channels and customer regions is connected. Perhaps you’ve got some information … Read More

When we ask if our observations align with expectations, we are performing a chi-square goodness of fit test. For example, imagine you think a mixed … Read More