Business Analytics - R Language
Course Overview
This course aims to provide students with a comprehensive introduction to R programming, covering its basics to more advanced topics such as data visualization and statistical analysis. Students will engage in practical exercises, hands-on activities, and real-world applications to enhance their proficiency in R.
Course Objective
- Understand the basics of R programming and its environment.
- Learn to manipulate and analyze data using R.
- Develop skills in creating various types of plots and visualizations.
- Apply R for statistical analysis and data handling.
- Work on a project to implement R skills in a practical scenario.
Pedagogy:s
- Lectures: Theoretical foundations and key concepts will be taught through interactive lectures.
- Hands-on Activities: Practical activities to apply learning in real-world scenarios.
- Case Studies: Real-world examples to illustrate the application of R programming concepts.
- Group Discussions: Collaborative discussions to enhance understanding and encourage diverse perspectives.
- Project: An end-of-course project to demonstrate the application of R programming skills.
Course Outcomes
By the end of the course, students will be able to:
- Navigate and utilize the R programming environment effectively.
- Use R for data manipulation, analysis, and visualization.
- Implement various data types, loops, and functions in R.
- Create and interpret different types of plots and charts using R.
- Conduct statistical analysis using R.
- Present a project demonstrating practical use of R programming skills.
Session Plan
Business Analytics - R Langugae Syllabus T29
| Session No. | Topics | Activities |
|---|---|---|
| Session No. | Topic | Activities |
| Class 1 | R HOME | Introduction and Setup |
| Class 2 | R Intro | Lecture and Practical Exercise |
| Class 3 | R Get Started | Hands-on Activity |
| Class 4 | R Syntax | Lecture and Exercise |
| Class 5 | R Comments | Practical Activity |
| Class 6 | R Variables | Hands-on Activity |
| Class 7 | R Data Types | Lecture and Exercise |
| Class 8 | R Numbers | Practical Exercise |
| Class 9 | R Math | Hands-on Activity |
| Class 10 | R Strings | Lecture and Exercise |
| Class 11 | R Logical/Booleans | Practical Activity |
| Class 12 | R Operators | Lecture and Exercise |
| Class 13 | R If...Else | Hands-on Activity |
| Class 14 | R While Loop | Lecture and Exercise |
| Class 15 | R For Loop | Practical Activity |
| Class 16 | R Functions | Lecture and Exercise |
| Class 17 | R Vectors | Hands-on Activity |
| Class 18 | R Lists | Lecture and Exercise |
| Class 19 | R Matrices | Practical Exercise |
| Class 20 | R Arrays | Hands-on Activity |
| Class 21 | R Data Frames | Lecture and Exercise |
| Class 22 | R Factors | Practical Activity |
| Class 23 | R Plot | Hands-on Activity |
| Class 24 | R Line | Lecture and Exercise |
| Class 25 | R Scatterplot | Practical Exercise |
| Class 26 | R Pie Charts | Hands-on Activity |
| Class 27 | R Bars | Lecture and Exercise |
| Class 28 | Statistics Intro | Practical Activity |
| Class 29 | R Data Set | Hands-on Activity |
| Class 30 | R Max and Min | Lecture and Exercise |
| Class 31 | R Mean Median Mode | Practical Activity |
| Class 32 | R Percentiles | Hands-on Activity |
| Class 33 | Project Presentation | Presentation |
| Class 34 | Project Presentation | Presentation |
References:
- Adler, J. (2010). R in a Nutshell: A Desktop Quick Reference. O'Reilly Media.
- Kabacoff, R. I. (2015). R in Action: Data Analysis and Graphics with R. Manning Publications.
Textbooks:
- Matloff, N. (2011). The Art of R Programming: A Tour of Statistical Software Design. No Starch Press.
- Wickham, H., & Grolemund, G. (2016). R for Data Science: Import, Tidy, Transform, Visualize, and Model Data. O'Reilly Media.
Useful Hyperlinks:
- R Project for Statistical Computing - https://www.r-project.org/
- R Studio - https://www.rstudio.com/
- R Documentation
Software for R Practice
- R Language