Lab -- Business Analytics Conceptual Competency

By Dave Eargle

Your assignment is to read the entirety of Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking 1st Edition (Amazon Link)

This is “The Book” to read for your program. I think you should have read it before starting any classes. Grokking it will endow you with the ability to:

  • not sound like a moron when talking about predictive analytics
  • get the big picture about business analytics
  • understand the difference between supervised / unsupervised

A lot of the courses in your program focus on interpreting predictive models, aka “prescriptive analytics.” You miss out on the predictive analytics side. The predictive side is very important, and is the core of “machine learning”. Predictive analytics focuses on model evaluation, model training approaches, model deployment and use. The book covers the theory and the basics of the underlying math in a very approachable way – written for a managerial audience. You will see big sections that say “warning! Math ahead, not necessary to read to understand the content!” But you must read and understand these.

Seriously, I cannot endorse this book highly enough. Your deadline for reading it is: yesterday. Always yesterday. Read it. Be able to teach each chapter.

Deliverable

On my business analytics GitHub Pages website, you will see a list of topics in the order that I taught them, and corresponding readings from “the book.” Many of the topics have corresponding quizzes on canvas – I pulled out questions from the two exams over the course, and I grouped them by class topic. (Students complained that the class content and exams were too complex for ugrads, and that they would better fit a graduate program. So here we are!)

I will formally assign the canvas quizzes during the semester. You may take them as many times as you like. You should be able to see the right answers after you submit. The goal is that you understand why any given MC option is right or wrong. To the degree that you can do this, you will have met the learning objective for this lab. Take note about the things that are confusing, and we can discuss them in class.