I recently completed 5130 Data Analytics I which was basically a crash course in basic R and Statistics 101. The professor was a full time data scientiest for Lockheed Martin, so, he definitely took an applied approach throughout the course. The course utilized OpenIntro Statistics as the main textbook. It is open source and had a lot of supplementary resources like videos, slides and labs for each chapter. Although it is not free, these resources definitely make it worth the price and more!

Although we mostly utilized Excel at the start of the course, it soon became my applied introduction to the R programming language! I’m thankful that I discovered Posit.cloud. The site was super helpful and intuitive in getting me working with and learning to work with R. The tutorials and cheat sheets were super helpful and best of all, the cloud based set up gets you to work right away with no complicated set ups, downloads, etc.

The course was an applied overview of quantitative methods essential for analyzing data, with an emphasis on business and industry applications. Topics included identification of appropriate metrics and measurement methods, descriptive and inferential statistics, experimental design, parametric and non-parametric tests, simulation, and linear and logistic regression, categorical data analysis, and select unsupervised learning techniques.

Tools Utilized: Excel, R statistical programming language, POSIT (web-based R-Studio application)
Skills Acquired: Basic descriptive and inferential statistics, experimental design, linear/logistic regression, supervised and unsupervised learning techniques