This workshop will cover regression analysis using linear models and least squares in Python.  We will discuss the goals and main use-cases for linear regression, and how to interpret a fitted linear model.  We will then discuss methods for fitting more complex models with larger data sets, including the use of interactions, dummy-coding of categorical […]

This workshop will cover fitting generalized linear models (GLMs) in Python, using the Statsmodels package.  We will cover logistic regression, but the Poisson, negative binomial, and gamma regression. We will provide an overview of the underlying foundation for GLMs, focusing on the mean/variance relationship and the link function.  Participants should have familiarity with linear regression […]

In this workshop we will discuss the concept of dependency management, with the primary focus on build dependencies between software components.  We will learn how to express the dependencies and how to automate the software building process using Make utility and language.  We will go through hands-on exercises and will see how expressing the dependencies […]

People using R for applied research are often not taught basic programming practices such as writing functions, efficient iterative processing, vectorization, and other practices that would make their research far more efficient and reproducible.  Understandably, focus is on basic data manipulation and getting model results.  Unfortunately, this can mean the data isn’t as explored as […]

GEE is an extension of the generalized linear modeling (GLM) framework for dependent data.  GEE can be used with longitudinal data, clustered data, and other forms of dependent data where a GLM may not be appropriate.  In this workshop we will discuss fitting models using GEE in Python with the Statsmodels package. We will briefly […]

In the R by Example series of workshops, we’ll discuss example analyses in R as a vehicle for learning  commonly used tools and programming patterns.  The “Functional Programming with dplyr” workshop will initially focus on analyzing winter home temperatures in the US using data from the Residential Energy Consumption Survey (https://www.eia.gov/consumption/residential/).  We’ll use the dplyr package for data […]

Audience: Those who have never used Stata before but wish to learn. By the end of the workshop, participants will be able to: Work with Stata, including using Do-files and using the help system Get data into Stata and manage your data files Establish familiarity with your data Clean the data to prepare it for […]

Multilevel modeling is the state-of-the-art approach for handling data with complex dependence structure in a regression analysis.  This workshop will discuss fitting multilevel models in Python using the Statsmodels package. We will discuss the motivation and main use cases for multilevel modeling, and illustrate by example how to fit linear and generalized linear mixed models. […]

In this workshop we will use Make to manage build dependency in a multi-file, multi-language software project.  We will learn how to use Make functions, automatically generate dependencies, and inquire the operating system about available packages and libraries.  Also, we will briefly review alternative build dependency managers. At the end of the workshop you will […]

This workshop will be heavy on conceptual understanding of basic regression modeling, but with demonstration of activities both essential and tangential to good modeling practice. GLM, model interpretation, model comparison, model debugging, model criticism and more will be covered. Prereq: Some experience using R is required (R I, preferably R II workshops), as well as […]