Analytics at Sauder
Analytics@Sauder is a recent University of British Columbia (UBC) Teaching and Learning Enhancement Fund (TLEF) sponsored project.
Browse NotebooksOur mission
The objective of Analytics@Sauder is to curate a collection of open-source business analytics tools and resources, to promote opportunities for hands-on learning, to foster an online, academic community of business analytics, and to facilitate conversations around data analytics within a broader business context. We hope that the UBC Business Analytics Open Learning Resources can provide a platform of mutual learning: while we hope that this Project can be helpful to business analytics professionals of all skill levels, we appreciate all feedback on our resources so that we can continue to improve what we do. We welcome suggestions, contributions, and collaborations of all kinds.
Navigate This Website
The Notebooks page contains a list of Jupyter Notebooks with applications of analytics in various business domains. Detailed information on how to contribute to our repository can be found under the Resources page, along with tutorials for Git, GitHub, Jupyter Notebook, Syzygy, and Binder.
For Educators
We invite educators to borrow from and contribute to this platform by referring to the various Notebooks for use inside and outside classrooms, providing feedback through our Blog and GitHub, and contacting us with any helpful resources especially data, scripts, and Notebooks. We see Analytics@Sauder as a living learning tool that is constantly evolving and improving. By navigating to the Notebooks page, you can find a collection of Business Analytics Notebooks organized by Topics and Skills respectively. It is organized in this way to help students think about how analytics can be applied to different business domains, and at the same time, practice skills that will aid in the development of business insights. We value any feedback or suggestions for these Notebooks, and we encourage instructors to submit Issues and Pull Requests via GitHub, which you can learn more about on the Resources page.
Latest From Our Blog
Latest Notebooks
Multiple Linear Regression
RegressionBy: Hao Zheng
A regression is among one of the most commonly used methods when it comes to analysts trying to describe the result of an event, such as the effect of different characteristics on housing prices, which is what we are going to focus on in this Notebook.
Conjoint Analysis
Regression MarketingBy: Kemjika Ananaba
In this Project, we will learn about conjoint analysis and its application when introducing a new product into the market. Rank-based conjoint analysis is carried out in this Project using multiple linear regression.
Common Probability Distributions
Data ManipulationBy: Hossein Piri, Steven Shechter
This notebook describes probability distributions often used in simulation modeling, demonstrates how to generate random variables from these distributions, and visualizes the distributions through their density functions and histograms from sampled data.