## January 2020

## Introduction to Julia

This workshop will introduce the Julia programming language, with a focus on using Julia for data analysis. No prior exposure to Julia is needed. We will discuss some aspects of…

## Introduction to SPSS

Audience: Never before SPSS users who will be using SPSS for Windows. Those using SPSS for Unix or Macintosh should email the instructor at cpow@umich.edu before enrolling. Fundamentals This portion introduces SPSS for Windows, the…

## R I: Data Wrangling

This workshop will delve into common data processing and exploration techniques using R. The main focus will be on constructing and manipulating R data objects, and using packages that enhance…

## Linear regression analysis in Python

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…

## R by Example: Analyzing RECS using tidyverse

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 “Analyzing RECS using tidyverse” workshop will…

## February 2020

## R by Example: Analyzing RECS using data.table

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 “Analyzing RECS using data.table” workshop will…

## Regression analysis with Generalized Linear Models in Python

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…

## Introduction to Matlab

This workshop will introduce you to Matlab. We will look at general coding syntax, matrix operations, writing functions, symbolic capabilities, etc. Computers will be available to complete exercises.

## Basics of automatic dependency management with Make

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…

## R II: Programming

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…

## Generalized estimating equations in Python

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…

## Introduction to SAS: Basic Data Manipulating, Summarizing, and Graphing

Prerequisites: Familiarity with basic statistical calculations and graphs is helpful. In this one-day, six-hour workshop we will discuss the basics of using SAS for data analysis. The workshop is held…

## R by Example: Functional Programming with dplyr

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…

## Introduction to Stata

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…

## Multilevel models in Python

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.…

## Building software projects with Make: beyond basics

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…

## March 2020

## Introduction to Python’s NumPy library

This workshop will introduce you to the NumPy library in Python, which is useful in scientific computing. We will cover NumPy’s n-dimensional array object and associated functions in depth, along…

## R by Example: Functional Programming with data.table

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…

## Survival analysis in Python

Survival analysis is used when working with data that may be censored, as often is the case in studies of human subjects with incomplete follow-up. The presence of censoring makes…

## Introduction to SAS: Simple Inference Procedures

Prerequisites: Participant should have some familiarity with introductory statistics and be able to load data into and perform basic data manipulations in SAS. In this one-day, six-hour workshop we will…

## Building software projects: Use CMake to build the building plan!

This workshop is a continuation of the previous workshop “Building software projects with Make”. Make helps us to express dependencies within our projects, but what about external dependencies? Also, writing…

## Go for data processing Part 1

This is a two-session workshop on the use of Go for data processing. Go is an open source language developed for general-purpose programming. It is not more difficult to learn…

## Machine Learning in R

In this workshop, we’ll first discuss core machine learning concepts such as: choosing loss functions and evaluation metrics; splitting the data into training, validation, and testing sets; and cross-validation patterns…

## Go for data processing Part 2

This is a two-session workshop on the use of Go for data processing. Go is an open source language developed for general-purpose programming. It is not more difficult to learn…

## Introduction to Deep Neural Networks with Keras/TensorFlow

Deep Neural Networks (DNNs) are used as a machine learning method for both regression and classification problems. Keras is a high-level, Python interface running on top of multiple neural network…

## Building software projects: CMake is more than a build tool

This workshop is a continuation of the previous workshop “Building software projects: use CMake to build the building plan”. In this workshop, we will see that CMake is not just…

## April 2020

## Mediation analysis in Python

Mediation analysis is a set of tools for exploring hypotheses about causal pathways, with a special focus on differentiating “direct” from “mediated” associations between an exposure and an outcome. Many…

## Statistical analysis with missing data in Python

Missing data arise in many fields of research, and a large body of statistical tools has been developed to facilitate statistical analysis in the presence of missing data. Here we…