Did you know that there is no assumption in regression and ANOVA that the dependent variable follow a normal distribution? Really.

In fact, while it doesn't happen often, it can happen that a non-normal dependent variable--often a bimodal variable--still meets the assumptions of the model.

I have talked with many researchers who are checking the wrong assumptions of the GLM. Or they're checking the right assumptions, but with over-conservative tests that find every data set fails to meet assumptions.

It's not surprising. Read any two statistics textbooks and they'll have a different list of assumptions. And list different ways to test them.

It's because while some of the assumptions are explicit, others are just implicit in the way the model is conceptualized. And some data issues, such as multicollinearity, while important to consider, are not actually assumptions of the model.

In this workshop, we will investigate each of the assumptions of the GLM so they make sense. You'll see they really aren't just a list of arbitrary rules.

You will get an accurate understanding of each of the assumptions, both implicit and explicit. In just two hours, you will learn:

• what each assumption really means
  
  
• why each assumption is important to maintain the integrity of the model and the accuracy of the p-values
  
  
• The consequences to the p-values of not meeting the assumption
  
  
• how to check each assumption, some with tests, and some with plots
  
  
• how to construct and read residual plots--how "robust" of a departure from normality or constant variance is acceptable
  
  
• common situations in which assumptions often fail
  
  
• what your options are if the assumption isn't met

• Will need to implement either linear regression or ANOVA soon, and want to be sure you're checking assumptions correctly
  
  
• Have conducted a linear model in the past and are confused by the different things you've heard about its assumptions and how to check them
  
  
• Are about to defend your dissertation and want to be sure you thoroughly understand your analyses well enough to defend your decisions to your committee
  
  
• Would like to learn as much as you can about the general linear model, so that you can apply it, and learn its extensions, with confidence and real understanding

Prerequisites

• Although we will use SPSS to show the examples, the focus here is not on the software. This workshop will be useful to anyone using any software. That said, you should be familiar with running an ANOVA or linear regression in some statistical software.
  
  
• You will get the most out of the workshop if you have had at least two statistics classes and some experience in data analysis.

• One 2-hour live webinar workshop session.  The session will contain a presentation and time for questions.  You will hear me and see exactly what is happening on my screen.

• A 60-minute Q&A session September 23 at 12pm, noon eastern. Just your questions and my answers. This is one week later, so you have a chance to try things out on your own data, then come back with questions. It's when you use these techniques on your own data that you cement your learning.
  
  
• PDF handouts of the presentation, which will be available ahead of time, on which you can take notes.
  
  
• SPSS data files and syntax code to run, explore, and practice all of the examples yourself.
  
  
• Video Recordings of each workshop session made available within 48 hours.
  
  
• Access to our central Workshop Basecamp. This is a web based location, where you can post questions, get call-in information for each webinar session, and download handouts and recordings.
  
  
• The opportunitiy to ask questions about implementing these techniques in your own analyses in addition to general questions about the topic.  (But please keep questions to the topic of the workshop so that they’re useful for everyone). 
  
  
• Exercises, with answers.  (Yes, homework!).  It’s optional, but you’ll get more out of the workshop if you participate fully by doing the exercises.  You can use one of the data sets provided, or your own.

Your registration fee is fully refundable up to 72 hours in advance minus a $25 administration fee. Because you will still receive the recorded video, no refunds will be granted after the program begins.

That said, your satisfaction is guaranteed. If you participate in the full workshop and find you are not satisfied for any reason, we will give you a full refund. Just notify us within 90 days of the conclusion of the program.