In leonawicz/uafrstat: R Package for STAT Course

tutorial::go_interactive()
knitr::opts_chunk$set(
  collapse = TRUE, comment = "#>", fig.path = "man/figures/README-",
  message = FALSE, warning = FALSE, error = FALSE, tidy = TRUE
)

Introduction to R Programming

The best way to get started is to look ahead to see not only where you will begin but also what you will build up to. Here is a tentative week by week schedule providing an overview of what you will be doing throughout this course.

Schedule overview

weeks <- 1:15
topics <- c("Software installation. Introduction to R, RStudio, GitHub and DataCamp. Overview of R data types.",
            "Basic data import/export, manipulation and plotting",
            "More data manipulation and plotting",
            "Even more data manipulation and plotting",
            "Basics of control flow, loops and functions",
            "Basic probability and statistics",
            "Intro to dynamic reports and markdown",
            "Intro to Shiny apps",
            "More with Shiny",
            "Using Shiny and Rmarkdown together",
            "Creating and validating R packages",
            "Package and function documentation",
            "Package development continued",
            "Final projects",
            "Final projects")
packages <- c(rep("", 2), 
              "dplyr, purrr, ggplot2, tibble",
              "",
              "",
              "",
              "knitr, rmarkdown",
              "shiny and related packages",
              "", "",
              "devtools, usethis",
              "roxygen2, pkgdown",
              "", "", "")
chapters <- c("R4DS Ch. 1, 2, 4, 20; AR: Data structures (optional)", 
              "R4DS: Ch. 6, 8",
              "R4DS: Ch. 3, 5, 7, 17 - 18", 
              "R4DS: Ch. 10, 11 - 12",
              "R4DS: Ch. 19, 21",
              "(optional: R4DS: Ch. 13 - 16)",
              "R4DS: Ch. 26 - 28",
              "",
              "",
              "R4DS: Ch. 29 - 30",
              "RP: Ch. 1 - 4, 8",
              "RP: Ch. 5 - 6",
              "", "", "")
datacamp <- c(paste("Ch.", 1:6), rep("", 9))
projects <- c(rep("", 7), "Project 1", rep("", 2), "Project 2", rep("", 3), "Final project")
x <- tibble::data_frame(Week = weeks, Topics = topics, `Key packages` = packages, 
                        DataCamp = datacamp, Reading = chapters,
                        `Key due dates` = projects)
knitr::kable(x)

Reading key

• R4DS: R for data science
• RP: R packages
• AR: Advanced R

See the course syllabus for details.

Additional details

First, note that many chapters in the primary text are fairly short and/or filled with code blocks, printed console output and plots. Don't stress if it looks like the number of chapters listed for a given week is unmanageable. It's manageable.

Weeks 1 - 6 focus on the basics of R programming, gets you familiar with the RStudio IDE, and using GitHub to track, back up and share your work. Weeks 7 - 10 focus on publishing your work (R code, data, results) online in both static and interactive publication formats. Weeks 11 - 12 introduce you to the process and best practices of creating your own R packages. Weeks 13 and 14 are optional and time-permitting, but continue with enhancing your ability to develop solid, dependable R packages to encapsulate and document the R code you write for your various projects and analyses. The final week is devoted to sharing final projects with classmates.

Text chapters listed as optional are just that, but also highly recommended or I wouldn't mention them. Even if some content in them seems challenging, I encourage everyone to push themselves. Don't be shy of the title of the book, "Advanced R". You may find that some sections are easier than you expect and help clarify details that are relatively glossed over or ignored in the main text.

leonawicz/uafrstat documentation built on May 30, 2019, 6:58 p.m.