Whenever you run multiple statistical tests on the same set of data, you run into the problem of the Familywise Error Rate. What this means is that the true probability of a type 1 error somewhere in the family of tests you’re running is actually higher than the alpha=.05 you’re using for any given test. This is a complicated and controversial issue in statistics — even statisticians argue about whether it’s a problem, when it’s a problem, and what to do about it.

Logistic Regression can be used only for binary dependent variables. It can be invoked using the menu choices at right or through the LOGISTIC REGRESSION syntax command. The dependent variable must have only two values. If you specify a variable with more than two, you'll get an error. One big advantage of this procedure is it allows you to build successive models by entering a group of predictors at a time.

Cluster analysis classifies individuals into two or more unknown groups based on a set of numerical variables. It is related to, but distinct from, a few other multivariate techniques including discriminant Function Analysis..

When we talk about moderation, though, there is a specific role to X and Z. One is assigned as the Independent Variable and the other as the Moderator. The Independent Variable is an independent variable based on the third implication listed above: its effect is of primary interest.

In Part 14, let’s see how to create pie charts in R. Let’s create a simple pie chart using the pie() command. As always, we set up a vector of numbers and then we plot them.

One of our instructors–David Lillis–recently gave a talk in front of the Wellington R Users Group highlighting 15 Tips for using the R statistical programming language aimed at the beginner. Below is a video recording of his presentation…  

Complex Surveys use a sampling technique other than a simple random sample. Terms you may have heard in this area include cluster sampling, stratified sampling, oversampling, two-stage sampling, and primary sampling unit. Complex Samples require statistical methods that take the exact sampling design into account to ensure accurate results. This webinar, by guest presenter Dr. […]

In Part 13, let’s see how to create box plotsin R. Let’s create a simple box plot using the boxplot() command, which is easy to use. First, we set up a vector of numbers and then we plot them. Boxplots can be created for individual variables or for variables by group.

In Part 12, let’s see how to create histograms in R. Let’s create a simple histogram using the hist() command, which is easy to use, but actually quite sophisticated.

Multicollinearity isn’t an assumption of regression models; it’s a data issue. And while it can be seriously problematic, more often it’s just a nuisance.