by Kim Love and Karen Grace-Martin
Statistics terminology is confusing.
Sometimes different terms are used to mean the same thing, often in different fields of application. Sometimes the same term is used to mean different things. And sometimes very similar terms are used to describe related but distinct statistical concepts.
If you’ve been doing data analysis for long, you’ve probably had the ‘AHA’ moment where you realized statistical practice is a craft and not just a science. As with any craft, there are best practices that will save you a 
lot of pain and suffering and elevate the quality of your work. And yet, it’s likely that no one may have taught you these. I know I never had a class on this. (more…)
For nearly a hundred years the concept of “statistical significance” has been fundamental to statistics and to science. And for nearly that long, it has been controversial and misused as well. (more…)
It’s easy to make things complex without meaning to. Especially in statistical analysis.
Sometimes that complexity is unavoidable. You have ethical and practical constraints on your study design and variable measurement. Or the data just don’t behave as you expected. Or the only research question of interest is one that demands many variables.
But sometimes it isn’t. Seemingly innocuous decisions lead to complicated analyses. These decisions occur early in the design, research questions, or variable choice.
Just about everyone who does any data analysis has used a chi-square test. Probably because there are quite a few of them, and they’re all useful.
But it gets confusing because very often you’ll just hear them called “Chi-Square test” without their full, formal name. And without that context, it’s hard to tell exactly what hypothesis that test is testing. (more…)
One component often overlooked in the ‘Define & Design’ phase of a study, is writing the analysis plan. The statistical analysis plan integrates a lot of information about the study including the research question, study design, variables and data used, and the type of statistical analysis that will be conducted.