Stata allows you to describe, graph, manipulate and analyze your data in countless ways. But at times (many times) it can be very frustrating trying to create even the simplest results. Join us and learn how to reduce your future frustrations.
This one hour demonstration is for new and intermediate users of Stata. If you’re a beginner, the drop down commands can be extremely daunting.
If you’re an intermediate user and not constantly using Stata, it’s impossible to remember which commands generate the results you are looking to create.
This webinar, by guest presenter Jeff Meyer, will give you five actionable tips (and examples you can re-use) that will make your next analysis in Stata much simpler.
We’ll explore:
- Save time with a do-file to create the table you want exactly as you want.
- A few methods (some easier than others) to create dummy variables out of a categorical variable with several categories
- At least three ways to insert a table into a document
- Quickly alter the looks of your graphs through the use of macros
- How to aggregate data to the group level based on a number of parameters
Date: Wednesday, July 29, 2015
Time: 4pm EDT (New York time)
Cost: Free
***Note: This webinar has already taken place. Sign up below to get access to the video recording of the webinar.
Our next free webinar is titled: “Random Intercept and Random Slope Models” and is coming up in August
Jeff Meyer is a statistical consultant with The Analysis Factor, a stats mentor for Statistically Speaking membership, and a workshop instructor. Read more about Jeff here.
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. Trent Buskirk, will give you an overview of the common sampling techniques, and their effects on data analysis.
This webinar has already taken place. You can gain free access to a video recording of the webinar by completing the form below.
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).
But statistical software doesn’t always give us the effect sizes we need.
In this webinar, we will go over:
- The difference between standardized and unstandardized effect size statistics
- An overview of effect size statistics for some common analyses (there seem to be so many!)
- How to calculate these when your software doesn’t give them to you
This webinar has already taken place. You can gain free access to a video recording of the webinar by completing the form below.
Have you starting using R?
One secret to using any statistical software well and without frustration is learning the little “tricks” that make it easy to do the things you need to do.
This is especially true in R, which is constantly being updated.
In this webinar, R expert David Lillis will show you 10 tips for getting the most of R.
David Lillis has taught R to many researchers and statisticians. His company, Sigma Statistics and Research Limited, provides both on-line instruction and face-to-face workshops on R, and coding services in R. David holds a doctorate in applied statistics and is a frequent contributor to The Analysis Factor.
This webinar has already taken place. You can gain free access to a video recording of the webinar by completing the form below.
We also offer some online R workshops taught by David.
All statistical modeling–whether ANOVA, Multiple Regression, Poisson Regression, Multilevel Model–is about understanding the relationship between independent and dependent variables. The content differs, but as a data analyst, you need to follow the same 13 steps to complete your modeling.
This webinar will give you an overview of these 13 steps:
- what they are
- why each one is important
- the general order in which to do them
- on which steps the different types of modeling differ and where they’re the same
Having a road map for the steps to take will make your modeling more efficient and keep you on track.
This webinar has already taken place. You can gain free access to a video recording of the webinar by completing the form below.
Odds ratios are the bane of many data analysts. Interpreting them can be like learning a whole new language. This webinar will go over an example to show how to interpret the odds ratios in binary logistic regression. You will learn:
- how probability and odds both measure the same thing on different scales
- the meaning of odds
- how to interpret an odds ratio for continuous and categorical predictors in logistic regression
This webinar has already taken place. You can gain free access to a video recording of the webinar by completing the form below.
