courses for review by invited guests to our Learning Management System

Aim of Course:

To provide an easy introduction to statistical inference for a single variable.

Aim of Course:

This course, the second in a three-course sequence, provides an easy introduction to inference and association through a series of practical applications, based on the resampling/simulation approach.

Aim of Course:

This course will show you how to use R to create statistical models and use them to analyze data.

Aim of Course:

The goal of this course is to introduce the basics of programming in Python, on either Windows or Mac.  You will use both Jupyter notebooks and standard script editors, and work through simple arithmetic operations, statistical operations, variables, keywords, lists, arrays, and dictionaries.  You'll use conda to install modules and close with some data visualizations.

Aim of Course:

In this online course, "Programming 2:Python," you'll learn everything you need to get you started using Python for data analysis.  We'll review basic Python skills and data structures, move on to how to load data from different sources, rearrange and aggregate it, and finally how to analyze and visualize it to create high-quality products.

Aim of Course:

This course will provide the basics of vector and matrix algebra and operations necessary to understand multivariate statistical methods, including the notions of the matrix inverse, generalized inverse and eigenvalues and eigenvectors.

Aim of Course:

This course will show you how to use R to create statistical models and use them to analyze data.