Modern Languages Building (MLB), Room 2001A

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.

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…

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…

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…

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…

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,…

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…

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…

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…

Regular expressions are perfectly suited for people who like puzzles. Regular expressions are a sequence of characters used to define a search pattern. They are commonly used to do “find”…

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…