Business Analytics - Course Landing Page

Author

Ayush Patel

What you need before coming to class

Here are necessary computational set ups that are required before staring the course. I promise this will make your life easier.

R and RStudio

This course is being taught using R statistical programming language. It is essential that you have R installed on your machines. (Yes! You need to bring your laptops to class. Yes, Everyday!). Strictly speaking, RStudio is not necessary for the course. However, having RStudio will make your life convenient.

If you have R and RStudio installed on your laptops that is great. Please, make sure these are fairly recent versions.

If you do not have R and/or RStudio installed, see the following:

  • Get R from Here
  • Get RStudio from Here. Only download RStudio. No need to download R if you have it.

Libraries

There are a certain packages that we will use frequently use in class. Copy the following code, paste it in your console and execute it. This will install packages that you do not have.

install.packages("pacman")

pacman::p_load(tidyverse, rmarkdown, 
               tinytex, ISLR, ISLR2, 
               openintro, opendatatoronto,
               causaldata)

Basics of R programming

It is imperative that you know the basics of R programming. That means ability to basic data wrangling tasks and basic visualizations. I recommend you go through these if you are not confident:

  • This is a small book. Can be completed in one or two days at an easy pace. It will start with all elementary topics.
  • Read and practice chapters on data transformation and visualization from R for data science. Chapters 3,9 and 10.
  • You can also access Coursera. It is free for students at GIPE. There are several courses available to get upto seed with data wrangling and visualization.

Lecture Slides

You will find all lecture slides populated here.

References

Here are various resources on R programming, and statistics and methods.

For R programming:

  • R for Data Science. This book will take you through all programming techniques required to start applying data science methods. This is not a book on data science. This books helps you learn programming that this needed to do data science.

  • Hands-on Programming with R. Similar motivations for using this book as the one above. This books starts at scratch.

  • Fundamentals of Data Visualizations. This book covers programming techniques and concepts related to data viz.

  • R Graphics Cookbook. Everything you will ever need to learn the fundamentals and more of visualization using R.

  • Quarto website for literate programming.

  • RMarkdown Cookbook. The book for all details about RMarkdown.

For Stats and Methods: