From the course: R Essential Training Part 2: Modeling Data

Model data with R

From the course: R Essential Training Part 2: Modeling Data

Start my 1-month free trial

Model data with R

“

- [Barton] Understanding what's happening with your customers, predicting outcomes for patients and more generally, making critical decisions is difficult given that there are so many possible courses of action, and essentially, infinite possible outcomes. But rather than crossing your fingers and hoping for the best, you can use data as a compass to help guide you through these demanding decisions. And one of the best ways to find direction in data is with R, that's a free, open-source programming language that was specifically designed for exploring and modeling data to help you hone in on the insight that you need. I'm Barton Poulson and in this course, part two of two courses on working with R, we'll take a look at how you can find meaning in data with R. Building on what we learned in part one, I'll show you how to get concise descriptions of your data, focus on important dimensions, and compute insightful statistical procedures, like correlations, the analysis of variants, and a diverse collection of predictive analytics such as hierarchical and K-means clustering, K-nearest neighbors classification, decision trees, and random forest models. Now this is an introductory course, so you don't need to have any experience with R in particular, aside from taking part one of this course on wrangling and visualizing data, and you don't need any special experience with computer programming in general. It's helpful, but not critical, to have some familiarity with the basic concepts of statistical analysis, but either way, I'll explain concepts thoroughly as we go through the course. You'll see the power and the flexibility of R and how it can help you find meaning in the data that's all around you. And so let's get started with R essential training part two, modeling data.

Contents