Basic Programming for Business Analytics
This course covers programming techniques for data management and analysis. The course is designed to introduce the fundamentals of programming for business analytics. These methods provide a powerful language for data management, visualization, and predictive modeling. Languages utilized include R, Python, and Spotfire. Students will progress to an intermediate level in writing R scripts.
Expected Learning Objectives
Upon completion of the course students will:
- Use RStudio, read R documentation, and write R scripts
- Use R programs to perform data manipulation/management and analysis tasks
- Produce basic graphics and more advanced graphics using ggplot2 library
- Report results of statistical analyses with R Markdown
- Learn about Python and Spotfire, understanding how to explore these powerful tools
- Develop professional skills in creative thinking, critical thinking, and self-directed learning
- Selection of Topics Covered:
- R Basics and Introduction to Data
- Data Frames
- R Programming Fundamentals
- R Packages and dplyr
- Data Manipulation
- Data Visualization
- Statistics and Comparison Tests
- Correlation and Regression
- Multiple Regression
- Data Modeling Languages and career progression
Course Pedagogy and Immersive/Experiential Activities
Classes utilize hands-on work with programming in statistical and business analytics and graphical representation. Examples covered in class are selected to be relevant to the student experience and for the career paths of our students.
Students are provided with class lessons, course materials, and additional resources. Homework is provided to students for the purpose of practicing the skills being learned in this class.
Grades are typically determined by performance in a series of homework assignments that progressively cover key concepts, three exams, and a large practical project allowing you to apply the principles and skills being learned within a simulated business scenario.