Events

  • 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 [email protected] before enrolling. Fundamentals This portion introduces SPSS for Windows, the menu and the help systems, the three main types of files used, and printing from within SPSS.  It then addresses defining variables, attaching labels, defining […]

    R I: Data Wrangling

    Modern Languages Building (MLB), Room 2001B

    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 and facilitate operations that typically arise when dealing with data, including faster I/O, variable creation and manipulation, and grouped operations, especially as a prelude to […]

    Linear regression analysis in Python

    Rackham Building, Earl Lewis Room, 3rd Floor East 915 E. Washington St., Ann Arbor, MI, United States

    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 […]

    R by Example: Analyzing RECS using tidyverse

    Modern Languages Building (MLB), Room 2001B

    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 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 tidyverse (tidyverse.org) throughout, relying on […]

  • Julia drop in coding session

    Weiser Hall, 6th Floor, 619 500 Church Street, Ann Arbor, MI, United States

    MIDAS and CSCAR will hold a drop-in coding session focusing on using the Julia programming language for basic data analysis.  No prior experience with Julia is expected.  The session will focus on analyzing large public AIS datasets recording the tracks of ships traveling in US coastal waters.  Participants can use (link below) as a starting […]

    R by Example: Analyzing RECS using data.table

    Modern Languages Building (MLB), Room 2001B

    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 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 data.table package for data manipulations […]

    Regression analysis with Generalized Linear Models in Python

    Rackham Building, Earl Lewis Room, 3rd Floor East 915 E. Washington St., Ann Arbor, MI, United States

    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 […]

    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

    Rackham Building, Earl Lewis Room, 3rd Floor East 915 E. Washington St., Ann Arbor, MI, United States

    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 […]

    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 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 […]