Business Strategy and Analytics Syllabus
- Email: anil[dot]doshi[at]ucl[dot]ac[dot]uk
- Course ID: MSIN0116 (UCL Moodle)
- Offered: December 2018
- Full Time: Weekdays
- Part Time: Weekends
- Hours: Morning session 9:00am - 12:30pm, afternoon session 2:00pm-5:30pm
I would like to make explicit some norms that I hope are wholly embraced in the classroom.
- Treat our time in the classroom as you would meeting with the executive team or board of directors of your company. This means listening to and respecting the perspectives of your peers. It also means speaking up and disagreeing when you have a different opinion.
- Arrive to class on time and prepared to contribute.
- Participating in class (both speaking and listening to your colleagues) is a critical component of this module.
- Do not wait until you have the perfect comment to raise your hand and speak in class.
- Take risks with your ideas.
- Speak in class if you have a question. If you have a question, it's very likely that your peers do as well.
- Embrace failure and the iterative nature of learning and discovery.
By taking this module, you are agreeing to maintain the highest level of academic and professional integrity. For your work, this means citing sources wherever appropriate and producing work that is your own. Cheating, plagiarizing, or misrepresenting one's work are a violation of our classroom's aspirational norms and the program's code of conduct.
Because we focus on underlying principles, we will not use of any specific software or tools. In the assignments, students will focus on conceptual application and interpretation of analytics-related approaches. The goal is to understand the problem and identify a path towards a solution.
For those who are interested in applications used for many of the approaches we will see in class, I would suggest taking a look at R or Python. Below are some resources as a start.
- RStudio. Integrated development environment (IDE) for the statistical programming language, R.
Data is everywhere online. If you want to explore data during or after our time together, I have assembled an list of data sources you can use as an initial point for your search.
While no books are required for this class, I recommend a selection of the following books to complement what you will see during the term.
- Diez, D. M., C. D. Barr, and M. Cetinkaya-Rundel (2015). OpenIntro Statistics. OpenIntro.
- Few, S. (2012). Show Me The Numbers: Designing Tables and Graphs to Enlighten. Burlingame, CA: Analytics Press.
- Gonick, L. and W. Smith (2000). Cartoon Guide to Statistics. New York: HarperPerennial. (Sounds like a silly book, but it is quite good)
- Grant, R. M. (2016). Contemporary Strategy Analysis. United Kingdom: John Wiley & Sons Ltd.
Assessment is based on an individual assignment (60%) and a team project (40%).
Teams will consist of three to four students (check with me if you want to form a team of five) and will work on devising a business plan that combines the strategy-related topics we cover in class with the analytics topics.
We will break down each day into six blocks of approximately 70 minutes and class time will be divided between interactive lectures and labs/investigations. Below is the the schedule.
|4||Data Fundamentals and Descriptive Analytics|
|6||Statistical Inference and Regression|
|8||Correlation vs Causation|
|10||Data-based Business Models|