Final Exam

The Final Exam is on Thu, Dec 10 @ 10:30am.

Click this Zoom link to join.

Review materials are available here and here.

If you are satisfied with your current grade, as shown in Bb, you may opt out of the final exam. Unless you have already communicated your plans, please contact me via email to confirm.

Best wishes for a safe and peaceful winter break.

Lesson 26: Review for Final Exam, Part 2

Zoom Meeting Link

Review:

• Part 1

Presentation:

• Video Recording
• Practice Final (20 points)

Assignment:

• Bb grade check
• Final Decision via Zoom Chat
• Complete a course evaluation
• Prepare for Final Exam Thu Dec 10 @ 10:30am on Zoom

Lesson 25: Review for Final Exam, Part 1

Zoom Meeting Link

Review:

• Assignment 10
• Final Exam
  • Thu Dec 10 @ 10:30am on Zoom
  • Review on Thu Dec 3

Presentation:

• Video Recording
• Review for Final Exam
  • Format
    • Spreadsheet Questions – produce a file
    • General Questions – short answer
    • Google Forms or similar
  • Pre-Midterm
    • Revisit the Midterm Review
    • Revisit the Midterm Practice Exam
    • Review your Midterm Exam and corrections
  • Post-Midterm
    • Simulation
    • Spreadsheets
    • Prepare to create or modify
    • Dice Simulation Example
    • Stock Market Simulation Example
      • Script provided

Assignment:

• Study for the final

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:

• Zoom Video Recording
• Statistics in Spreadsheets Part 1

Assignment:

• Complete Intro to Statistics in Spreadsheets
  • Chapter 1 and 2 before class Thu
  • Chapter 3 and 4 before Thanksgiving Break

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

Zoom Meeting Link

Review:

• Remote Learning (thru end of semester)
• Stock + Bond Simulation

Presentation:

• Zoom recording
• Stock Market (or Retirement Portfolio) Simulation

Assignment:

• Assignment 9
  • Complete the Stock Market (or Retirement Portfolio) Simulation
  • Due Mon Nov 16 at 11:59pm
  • Submit Here
• 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

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.

Lesson 19: Election Simulation

Review:

• Election forecasting
• Zoom on Thu
• Assignments 8.1 and 8.2
• Stock Market Simulation

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

Lesson 18: Election Forecasting

Review:

• Assignment 7

Presentation:

• Latest Polls
• Election Forecasting by Nate Silver
• Google Surveys

Assignment:

• Forecast the Electoral Map
  • Save the link to your forecast
  • Submit your link here
  • Due Mon Nov 2 by 11:59pm

• Write a 300 word (1-2 page) essay
  • Choose any “bullet point” subtopic in this article
  • See video for details
  • Submit your essay here
  • Due Thu Nov 5 by 11:59pm