DAT 204 - R for Analytics Credits: 3 3 Skills Lab Hours
Prerequisites: DAT 119 , demonstration of basic proficiency in any other programming language as verified by instructor
Description This course guides students in the use of the R programming language for data analysis. After exploring the fundamentals of the R language and essential data structures, students learn to manipulate structured data in R in preparation for statistical analysis. Standard statistical data analysis techniques are implemented in R. In addition to mechanical fundamentals, this course is rooted in building skills in sound data analytical thinking: surveying data sets, generating compelling inquiry questions, conducting rigorous quantitative analysis, drawing conclusions rooted in reproducible findings and discussing the limitations of this analysis with a lay audience. Learning Outcomes Upon successful completion of the course, the student will:
- Execute essential operations in RStudio including loading and viewing structured data files, reading data into R objects and manipulating data.
- Demonstrate an understanding of the basics in R programming in terms of constructs, control statements, functions and libraries.
- Generate basic plots and descriptive statistics in R for structured data sets.
- Implement an end-to-end data analysis process.
- Write reusable code that meets program specifications and follows best practices for reproducible data workflows.
Listed Topics
- Integrated development environment
- Structured data
- Vectors
- Objects
- Arrays and matrices
- Data frames
- Functions
- Regressions
- Plots
Reference Materials Free online resources for both learning R fundamentals and conducting advanced analysis Students who successfully complete this course acquire general knowledge, skills and abilities that align with CCAC’s definition of an educated person. Specifically, this course fulfills these General Education Goals: - Critical Thinking & Problem Solving
- Quantitative & Scientific Reasoning
Approved By: Dr. Quintin B. Bullock Date Approved: 12/14/2020 Last Reviewed: 12/14/2020
Course and Section Search
Add to Portfolio (opens a new window)
|