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Linear regression is a useful and widely used statistical learning method and serves as a good jumping-off point for newer predictive analytic approaches. Check out the newly added linear regression tutorial that covers the basics of this power analytic technique.
Analysts are often trained to handle tabular or rectangular data that are mostly numeric, but much of the data proliferating today is unstructured and typically text-heavy. Many of us who work in analytic fields are not trained in even simple interpretation of natural language. Fortunately, many of the principles used to organize, analyze, and visualize tabular data can be applied to unstructured text to extract meaning from this information.
Check out the first couple text mining tutorials that have been released. Additional tutorials will be released in the coming weeks.
A.A. Milne said that “organization is what you do before you do something, so that when you do it, it is not all mixed up.” If you are not careful your data analyses can become an explosion of data files, R scripts, ggplot graphs, and final reports. Each project evolves and mutates in its own way and keeping all the files associated with a project organized together is a wise practice. Furthermore, reproducibility is crucial in any analytic project.
RStudio provides several great options for improving your analytic workflow. This includes RStudio projects, R Markdown, and the newly released R Notebook. Check out the tutorials we just released on these tools and get your analytic workflow moving in the right direction before your next project!
Check out the latest tutorial on creating lollipop charts here. Enjoy!
UC BANA students, the Intro to R Bootcamp slides have been updated to reveal the solutions for each Your Turn! exercise. Just scroll down to the Schedule section and click on the icon for each session in and you’ll see the updated slides. I also add my code to the script files () so you can see my approach to many of the topics we covered. Enjoy!