"End? No, the journey doesn't end here."
--- J.R.R. Tolkien
After reading this chapter you will be able to:
R
programming language.So you've completed STAT 420, where do you go from here? Now that you understand the basics of linear modeling, there is a wide world of applied statistics waiting to be explored. We'll briefly detail some courses in the Statistics Department at the University of Illinois at Urbana-Champaign and discuss how they relate to what you have learned in STAT 420.
STAT 385, Statistics Programming Methods
lm()
, and performing simulation studies at scale are emphasized.STAT 425, Applied Regression and Design
STAT 424, Analysis of Variance
STAT 428, Statistical Computing
rdist()
functions actually generate random observations?STAT 426, Sampling and Categorical Data
STAT 430, Statistical Learning
R
, which is freely available, is used.STAT 429, Time Series Analysis
R
Examples, which is freely available, is often used.R
ResourcesIn this textbook, much of the data we have seen has been nice and tidy. It was rectangular where each row is an observation and each column is a variable. This is not always the case! Many packages have been developed to deal with data, and force it into a nice format, which is called tidy data, that we can then use for modeling. Often during analysis, this is where a large portion of your time will be spent.
The R
community has started to call this collection of packages the Tidyverse. It was once called the Hadleyverse, as Hadley Wickham has authored so many of the packages. Hadley is writing a book called R
for Data Science which describes the use of many of these packages. (And also how to use some to make the modeling process better!) This book is a great starting point for diving deeper into the R
community.
Also, don't forget that previously in this book we have outlined a large number of R
resources. Now that you've gotten started with R
many of these will be much more useful.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.