Module 8: Final Exam

Instructions for the final exam:

1. Create a video to answer six (6) essay questions.

• Each student will create a video in one of two (2) formats
  • Zoom style screen recording (like my lectures), or
  • Homemade video (simply use your phone)
• In your video you will provide oral answers to six (6) essay questions, posted in Bb.
• You don’t need to actually write out essay answers. Instead, answer the questions orally, using your own words.
• I want to see your face during the video. Don’t record audio only. This will help me better understand what you know and what you don’t know.
• You can use visual elements (e.g., data graphics, browse to a website, show an article, etc.) if it helps (but not required).
• Don’t read from a script, make it conversational, like answering questions in a job interview.
• Be thorough but don’t drone on and on without purpose, i.e., don’t confuse length of answer with quality.

2. Your video should be approximately 4-8 minutes in length.

• Speak clearly! If I can’t follow your commentary it may negatively impact your grade.
• Don’t go over 8 minutes.

3. Post your video and send me a link.

• Post your video on YouTube.
• (Yes, only YouTube. Why? Because if I allow you to post anywhere some will use an obscure platform and/or incompatible technology creating major headaches for me when grades are due.)
• Post the link to your video in Bb.
• Post the link only! Please do not try to actually upload your video on Bb.

Module 8: Final Exam

Review:

• Module 7

Presentation:

• Video Lecture
• Please ignore any references to the “Data Science for Business” assignment you may have seen. It’s not required.

Final Exam:

• I will be sharing a final exam in Google Sheets format on Bb.
• The Google Sheets file will contain all necessary data and instructions for completing the final.
• Once you have attempted all the exam questions you need to create a video presentation, as described below.

• Video Presentation Instructions:
  • Each student will create a video in one of 2 formats
    • Zoom style screen recording (like my lectures), or
    • Homemade video (use your phone)
  • Provide a “tour” of your final exam answers with the Google Sheets file displayed.
    • Explain how you approached each question and how you arrived at each answer.
    • Be honest and direct about what you do and don’t understand.
  • Your video should be 4-8 minutes in length.
    • Speak clearly! If I can’t follow your commentary it may negatively impact your grade.
    • Don’t go over 8 minutes.
  • Post your video on YouTube (yes, only YouTube is acceptable, to keep grading manageable).
  • Post your YouTube link in Bb.
  • Post the link only! Please do not try to actually upload the video to Bb.

Module 7: Simulation Part 2

Review:

• Module 6
• Here’s a video I recorded while helping a student: Chuck-a-Luck Help Session (28 min)

Presentation:

• Video Lecture (38 min)
  • In the beginning I refer to the Chuck-a-Luck Help Session video
• Random Variables
  • Discrete Random Variables
    • Probability distribution table
    • Dice Simulation
  • Continuous Random Variables
    • Stock Market simulation next week

Assignment:

• Stock Market Simulation in Sheets
  • Use Annual Stock Market Return data as a starting point
  • Assumptions
    • stock market returns are normally distributed
    • mean = 11.88%
    • standard deviation = 19.76%
• Modifications Part 1
  • Generate a 40-year simulation (instead of 30)
  • Modify the simulation to add $1,000 to the balance each year
  • Make a histogram of your ending balances
• Modifications Part 2
  • Add a “fixed income” (bonds) component to your simulation
  • Assumptions
    • bond market returns are normally distributed
    • mean = 7.88%
    • standard deviation = 6.86%
• Your “portfolio” should be 60% stocks and 40% bonds
  • How does the distribution of ending balances change?

Module 7: Data Science Toolkit

Review:

• Module 6
• DataCamp

Presentation:

• Video Lecture
• Data Science
  • Combination of statistics + programming with big data
  • Hot like computer software development in the 1990’s
  • Salaries are 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
• You don’t need to be a data scientist to ride this wave.
  • Steve Jobs never wrote code.
  • But Jobs knew the critical importance of customer experience.
  • And he knew marketing.
  • Data Scientists need partners with business expertise.

Assignment:

1. Search for job openings in the industry you chose in Module 5 using keywords “analytics” or “data science”.
2. Choose one of the job openings (whatever interests you most) and prepare a resume and cover letter you might submit to apply for the position. 
3. Keep your resume/cover honest – don’t misrepresent yourself – but try to work in some of the concepts and keywords you’ve learned in this class to make your application more appealing.
4. Submit one word doc with all three items below included.
   • Job advertisement
   • Resume
   • Cover letter

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

Module 6: Simulation Part 1

Review:

• Module 5

Presentation:

• Video Lecture
• Probability
  • Topic worthy of its own course
• Simulation
  • Random phenomenon
    • Individual outcomes are uncertain
    • Regular distribution of outcomes in large number of trials
  • Random number generation and stochastic processes
• Coin Toss Simulation
  • Demonstrate Coin Toss Simulation in Sheets
• Dice Roll Simulation
  • Demonstrate Simulation of rolling a pair dice in Sheets
  • Lucky 7 game
    • Roll a 7, win bet
    • Roll anything else (other than a 7), lose bet

Assignment:

• Replicate the Coin Toss simulation
  • 200 coin tosses (instead of 32)
  • reproduce the graph (showing 200 tosses)
• Replicate the “Lucky 7” simulation
  • 100 rolls (instead of 32)
  • Experiment with different Payoff Odds values (in cell K2)
  • What payoff odds would you suggest the Casino owner use to maximize revenue?
• Simulate Chuck-a-luck where the player rolls 3 dice
  • Here are the rules
  • Apply the following simplifying assumptions
    • If sum of 3 dice >10, player wins the “Big” (1 to 1 odds)
    • If the roll is three of a kind, player wins “Any Triple” (30 to 1 odds)
    • All other outcomes, player loses the bet
  • Will the “House” win money over time with these rules? Explain.