Module 6: Machine Learning
Review:
- Module 5
- Annotated Bibliography assignment
Presentation:
- Video Lecture
- Machine Learning
Assignment:
- Complete Machine Learning for Business (full course) on DataCamp
Author: Justin
Lesson 24: Statistics in Spreadsheets Part 2
Review:
- Statistics in Spreadsheets Part 1
- Chapter 3, Statistical Hypothesis Testing
Presentation:
- Zoom Recording
- Statistics in Spreadsheets Part 2
Assignment:
- Complete Statistics in Spreadsheets course
- Have a restful Thanksgiving break!
Lesson 23: Statistics in Spreadsheets Part 1
Review:
- Retirement Portfolio Simulation
- Data Science for Business
- Python
Presentation:
Assignment:
- Complete Intro to Statistics in Spreadsheets
- Chapter 1 and 2 before class Thu
- Chapter 3 and 4 before Thanksgiving Break
Module 5: Prescriptive Analytics and Optimization
Review:
- Module 4
Presentation:
- Video Lecture
- Prescriptive analytics
- Discrete mathematics
- Supply chain network optimization
- Inventory safety stock optimization
Assignment:
- Create an industry-specific “Analytics” Bibliography
- Choose an industry of interest (e.g., Sports, Health Care, Finance)
- Find written resources (journal or news articles, books, etc) using library databases, search engines, etc.
- List them and write a brief description of each resource
- Here’s a Help Sheet on how to write an annotated bibliography
- I recorded a video session with Librarian, Isabel Sotoluna for this assignment. Watch it!
Lesson 22: Data Science for Business
Review:
- Retirement portfolio simulation
Presentation:
- Zoom Recording
- Data Science
- Combination of statistics + programming with big data
- Hot like computer software development in the 1990’s
- Salaries are really high
- Python
- Programmers and companies are moving to Python
- Google uses Python extensively
- Python is gaining market share rapidly
- R
- Statistical Computing
- Growing fast but not as fast as Python
- Python is easier, more flexible
- R is more robust for heavy duty statistical modeling
- Many job ads ask for both R and Python skills
Assignment:
- Data Science for Business (entire course)
- Due Wed Nov 18 at 11:59pm
- (nothing to submit, I will check status on datacamp.com)
Lesson 21: Retirement Portfolio Simulation
Review:
- Remote Learning (thru end of semester)
- Stock + Bond Simulation
Presentation:
- Zoom recording
- Stock Market (or Retirement Portfolio) Simulation
Assignment:
- Assignment 9
- Required Elements
- 40-year time horizon
- Simulation count, n=100
- Ability to set/modify simulation parameters by changing cell values (not by editing formula)
- initial balance
- annual contribution
- stock/bond % allocation
- financial target, e.g., $1,000,000
- Functional start button to launch automation of simulation
- Display at end of simulation
- probability (%) of reaching financial target
- distribution of end balances on a histogram
- calculation of Max, Min, Mean, Median and Standard Deviation of end balances
Module 4: Predictive Analytics and Simulation
Review:
- Module 3
- Discussion
- Essays
Presentation:
- Video Lecture
- Simulation Overview
- Monte Carlo Simulation with Automation in Google Sheets
Assignment:
- Use the Stock and Bond Portfolio simulation
- Allocate % Stocks vs Bonds
- Enter Beginning Balance amount
- Enter Annual Contribution amount
- Enter Retirement Target amount
- Run Simulation
- Try different combinations and repeat
- Essay Questions (~1-page per question)
- Summarize your retirement savings expectations after experimenting with the simulation
- How could you use a comparable simulation approach in your current business or later in your professional life?
Lesson 20: Stock Market Simulation
Review:
- Election
- Status
- AP vs NYTimes vs FoxNews
- Shifts from 2016
- Simulation
- Polling error
- Grading
- Final Exam will take place during Finals week
Presentation:
- Video: https://youtu.be/rkLOtXtPnX8
- Back to the Stock Market Simulation
- Demonstrate adding/combining Bond Market returns
Assignment:
- Add a “fixed income” (bonds) component to your stock market simulation
- Assume bond market returns are normally distributed
- mean = 7.88%
- standard deviation = 6.86%
- Your “portfolio” allocation should be 60% stocks and 40% bonds
- Stock market and bond market returns should be combined each year and then reallocated in the next year.
- Assume bond market returns are normally distributed
Lesson 19: Election Simulation
Review:
Presentation:
- Video: https://youtu.be/ZnEwn2ouajA
- USC Dornsife Daybreak Poll
- Most accurate forecast in 2016?
- Election Simulation
- Simplifying assumptions
- Data sources
Activity:
- Incorporate electoral vote allocation in Maine and Nebraska
- And/or use different polling averages from a preferred source
- And/or use state specific margin of error quantities
Assignment:
- Vote
Module 3: Predictive Analytics and Time Series Forecasting
Review:
- Module 2
Presentation:
- Video Lecture
- Time Series Analysis
- Scatter plots
- Line plots
- Trend lines
- Linear
- Polynomial
- Forecasting
- Google Sheets
- Microsoft Excel
- Examples
Assignment:
- Reading
- Managerial Analytics, Ch. 6, Predictive Analytics, pp. 153-167
- Applied time series forecast efforts at Aftermarket Analytics
- Essay
- 1-2 page essay, similar to Module 2
- There are several issues (all very short, mostly graphical)
- Use these issues to summarize the impact of Covid-19 on the automotive aftermarket industry.
- How good were the forecasts?
- How could this series of articles be improved?