As a researcher, it’s critical for you to know more than one stat software. And R is a great “backup” program because it’s versatile, flexible, and FREE. R is virtually limitless… once you learn its quirks and ins and outs.…learn more

Effect Size Statistics are all the rage. Journal editors want to see them in every results section. You need them for performing sample size estimates (And editors want those too).…learn more

There are dozens of measures of association. Even just correlations come in many flavors: Pearson, Spearman, biserial, tetrachoric, squared multiple, to name a few.…learn more

Outliers. There are as many opinions on what to do about them as there are causes for them.…learn more

It turns out that having a good understanding of these rules (as well as actually remembering them) does come in handy when you’re doing data analysis.…learn more

We’ll clear up the ambiguity as to what exactly is a confidence interval and how to interpret them in a table and graph format.…learn more

We’ll review and compare what residuals are in linear regression, ANOVA, and generalized linear models…learn more

We’re going to take away that fog of confusion about exponents and logs and how they work. We’ll explain the logic and algebra of logs in plain English. …learn more

Knowing the level of measurement of a variable is crucial when working out how to analyze the variable.…learn more

You have many choices for software to analyze your data: R, SAS, SPSS, and Stata, among others. They are all quite good, but each has its own unique strengths and weaknesses…learn more

We will lay out the seven steps to run an accurate sample size estimate. Some of them are super easy. Others are much harder to do in practice than they look …learn more

We’ll review the framework of the traditional hypothesis test and compare it to the framework of the equivalence test and its one-sided cousin, the non-inferiority test.…learn more

There are many rules of thumb in statistical analysis that make decision making and understanding results much easier…learn more

This webinar will outline the advantages and disadvantages of the various data collection modes, types of samples available to target your population, how to obtain a representative sample, and how to avoid the pitfalls of bad questionnaire design…learn more

We will discuss how using effect size statistics will help us avoid the interpretational quagmire created by sample size…learn more

We will demonstrate how to calculate predicted means from a linear and a logistic regression model, then graph them…learn more

A central concept in statistics is a variable’s level of measurement. It’s so important to everything you do with data that it’s usually taught within the first week in every intro stats class…learn more