Co-listed with STAT 276W, STAT 476

This course offers an introduction to statistical computing in the R environment with the goal of exploratory analyses and effective communication using "tidyverse". With a main goal of communicating results to various audiences, this course will require writing via communicating results in a clear and effective manner based on the intended audience. This includes cleaning and preparing data for analysis, exploratory data analyses using simple graphics and tables, acknowledging and working with missing data, advanced graphics including map graphics to communicate results, statistical hypothesis generation & confirmation, introduction to the LaTeX typesetting language, advanced R Markdown formatting techniques (HTML, PDF, Word), figure and table creation with proper adaptive labels and captions, and bibliography with adaptive citations.

Basic skills with a test editor (such as Notepad) and Microsoft Excel are assumed. Students are expected to have basic skills in R and RStudio as covered in STAT 212. This course will be held in a computer lab with R and RStudio installed but students will need computer access outside of class.

Co-listed with STAT 276, STAT 476

This course offers an introduction to statistical computing in the R environment with the goal of exploratory analyses and effective communication using "tidyverse". With a main goal of communicating results to various audiences, this course will require writing via communicating results in a clear and effective manner based on the intended audience. This includes cleaning and preparing data for analysis, exploratory data analyses using simple graphics and tables, acknowledging and working with missing data, advanced graphics including map graphics to communicate results, statistical hypothesis generation & confirmation, introduction to the LaTeX typesetting language, advanced R Markdown formatting techniques (HTML, PDF, Word), figure and table creation with proper adaptive labels and captions, and bibliography with adaptive citations.

Basic skills with a test editor (such as Notepad) and Microsoft Excel are assumed. Students are expected to have basic skills in R and RStudio as covered in STAT 212. This course will be held in a computer lab with R and RStudio installed but students will need computer access outside of class.

Prerequisites: STT 211, 212, 213, or equivalent.

Description: This course offers an introduction to statistical computing in the R environment. To start, focus is placed on assigning objects, creating data structures, applying Boolean logic, importing and subsetting data, data manipulation (both long and short formats), and implementing elementary commands and built-in functions from R packages. In the second portion of the course, students learn more advanced topics of writing loops, developing functions, building graphics, debugging code, and text mining. Topics will be illustrated using key statistical tools, including basic data summarization and exploration, linear models, and simulations. The course will rely upon the use of R Markdown as an essential tool for effectively integrating R code and output into presentable reports. Basic skills with a text editor (such as Notepad) and Microsoft Excel are assumed, as is basic knowledge of statistical inference.

Prerequisites: STT 211, 212, 213, or equivalent.

Description: This course offers an introduction to statistical computing in the R environment. To start, focus is placed on assigning objects, creating data structures, applying Boolean logic, importing and subsetting data, data manipulation (both long and short formats), and implementing elementary commands and built-in functions from R packages. In the second portion of the course, students learn more advanced topics of writing loops, developing functions, building graphics, debugging code, and text mining. Topics will be illustrated using key statistical tools, including basic data summarization and exploration, linear models, and simulations. The course will rely upon the use of R Markdown as an essential tool for effectively integrating R code and output into presentable reports. Basic skills with a text editor (such as Notepad) and Microsoft Excel are assumed, as is basic knowledge of statistical inference.

Co-listed with STAT 276W, STAT 476

This course offers an introduction to statistical computing in the R environment with the goal of exploratory analyses and effective communication using "tidyverse". With a main goal of communicating results to various audiences, this course will require writing via communicating results in a clear and effective manner based on the intended audience. This includes cleaning and preparing data for analysis, exploratory data analyses using simple graphics and tables, acknowledging and working with missing data, advanced graphics including map graphics to communicate results, statistical hypothesis generation & confirmation, introduction to the LaTeX typesetting language, advanced R Markdown formatting techniques (HTML, PDF, Word), figure and table creation with proper adaptive labels and captions, and bibliography with adaptive citations.

Basic skills with a test editor (such as Notepad) and Microsoft Excel are assumed. Students are expected to have basic skills in R and RStudio as covered in STAT 212. This course will be held in a computer lab with R and RStudio installed but students will need computer access outside of class.

Co-listed with STAT 276, STAT 476

This course offers an introduction to statistical computing in the R environment with the goal of exploratory analyses and effective communication using "tidyverse". With a main goal of communicating results to various audiences, this course will require writing via communicating results in a clear and effective manner based on the intended audience. This includes cleaning and preparing data for analysis, exploratory data analyses using simple graphics and tables, acknowledging and working with missing data, advanced graphics including map graphics to communicate results, statistical hypothesis generation & confirmation, introduction to the LaTeX typesetting language, advanced R Markdown formatting techniques (HTML, PDF, Word), figure and table creation with proper adaptive labels and captions, and bibliography with adaptive citations.

Basic skills with a test editor (such as Notepad) and Microsoft Excel are assumed. Students are expected to have basic skills in R and RStudio as covered in STAT 212. This course will be held in a computer lab with R and RStudio installed but students will need computer access outside of class.