Lesson 24: Practice Final Exam

Review:

• Final Exam Topics
• Simulation Project, DataCamp and Overall Grades
• Course Evaluations
• Final Exam on Tue Apr 30 in HSB 117 (10:30a and 1:00p)

Presentation:

• Practice Final Exam

Activity:

• Complete Practice Final

Assignment:

• Study for Final Exam

Lesson 23: Final Review

Review:

• Exam 3 Results
• Grade Reports and Practice Final Exam on Wed Apr 24
• Final Exam on Tue Apr 30

Presentation:

• Review topics for Final Exam
  • Line Plots
  • Time Series Forecasting
    • Linear Trend
    • Polynomial Fit
  • Measuring Forecast Error
  • Multiple Regression
    • Coefficients for y-hat equation
    • t-statistics
    • p-values
    • R^2
    • Interaction variables
    • Dummy variables
  • Probability
    • Discrete
    • Continuous
  • Monte Carlo Simulation
  • Sheets
    • Random functions
    • If statements
    • Coin flip simulation
    • Dice simulation
    • Stock market simulations
  • Python
    • Basics
    • Lists
    • Functions
    • Packages
    • Matplotlib
    • Loops
    • Coin flip simulation
    • Dice simulation
    • Stock market simulations

Assignment:

• Study for Final Exam

Exam 3 Results

Exam 3
Mean	81.2
Standard Error	1.4
Median	80.5
Mode	80.0
Standard Deviation	11.4
Range	60.0
Minimum	40.0
Maximum	100.0
Sum	5601.5
Count	69.0

Lesson 22: Review for Exam 3

Review:

• Stock and Bond portfolio simulations
• Wed, Apr 17
  • Simulation assignment due in class
  • Exam 3

Presentation:

• Exam 3 Topics
  • Probability
    • Discrete vs Continuous
    • Sample Space
    • Short term uncertainty
    • Long term predictability
  • Monte Carlo Simulation
    • Randomization and repetition
    • Coin toss
    • Dice roll
    • Normal distribution
    • Stock market
  • Python
    • Basics
    • Lists
    • Functions
    • Packages
    • Matplotlib
    • Loops

Activity:

• Practice exam

Assignment:

• Complete stock + bond market simulations
• Study for Exam 3

Lesson 21: Simulation to Compare Retirement Savings Performance by Asset Allocations

Review:

• Loops
• Hacker Statistics Assignment
• Exam 3 on Wed, Apr 17
• Review for Exam 3 on Mon, Apr 15

Presentation:

• Stock market simulation project
  • Assumptions
    • Stock market returns are normally distributed with mean=11.84 and standard deviation=16.96
    • Aggregate bond returns are normally distributed with mean=7.88 and standard deviation=6.86
    • Initial investment balance = $10,000
    • Length of simulation = years until you reach age 65
    • Number of iterations for each simulation = 100
  • Produce 4 investment/retirement portfolio simulations
    1. 100% stocks + 0% bonds
    2. 80% stocks + 20% bonds
    3. 60% stocks + 40% bonds
    4. 40% stocks + 60% bonds
  • Comparison of simulation output
    • Create histograms to illustrate distribution of resulting ending balances
    • Calculate mean and standard deviation of ending balances
    • Produce 95% Confidence Intervals to estimate ending balances
    • Answer these 3 questions
      1. Which portfolios produced the highest and lowest ending balances?
      2. Which portfolios produced the most and least volatility?
      3. Which investment portfolio would you choose for your retirement? Explain why.
  • Deliverable
    • Produce a 1-page slide/doc to illustrate and explain results
    • Must include a link
      • to Repl.it program; or
      • to Google Sheets file
    • 1 piece of paper only (use front and back)
    • Due in class on Wed, Apr 17 (with Exam 3)

Assignment:

• Complete Hacker Statistics project and all DataCamp assignments
• Work on retirement simulation project

Lesson 20: Python Loops for Monte Carlo Simulation

Review:

• Intermediate Python for Data Science
  • Matplotlib
  • Dictionaries and Pandas
  • Logic, Control Flow and Filtering

Presentation:

• Intermediate Python for Data Science
  • Chapter 4: Loops

Activity:

• Complete Chapter 4: Loops

Assignment:

• Data Camp
  • Complete Chapter 5: Hacker Statistics
  • Due by 5p on Wed, Apr 10

 

Lesson 19: Data Visualization with Matplotlib in Python

Review:

• Intro to Python

Presentation:

• Intermediate Python for Data Science
• Chapter 1: Matplotlib
  • import matplotlib.pyplot as plt
  • Line plots
  • Scatter plots
  • Histograms
  • Labels, Axes, Other

Activity:

• Complete Chapter 1: Matplotlib
• Begin Chapter 2

Assignment:

• Complete Chapters 2 and 3 in Intermediate Python for Data Science
  • Chapter 2: Dictionaries and Pandas and
  • Chapter 3: Logic, Control Flow and Filtering
  • Due Mon Apr 8 before 5p

Lesson 18: Python Basics, Lists, Functions and Packages

Review:

• Simulation in Python
• DataCamp signup

Presentation:

• Introduction to Python Course in DataCamp
  • Python Basics
    • The Python Interface
    • Python as a Calculator
    • Variable Assignment
    • Calculations with variables
    • Other variable types
  • Python Lists
    • Create a list
    • List of lists
  • Python Functions and Packages
    • Familiar functions
    • List Methods
    • Import package
  • NumPy
    • Your First NumPy Array
    • Your First 2D NumPy Array
    • Average versus median
    • Explore baseball data

Assignment:

• Check your CSU-P email and verify/confirm enrollment in my DataCamp Class
• Complete the Introduction to Python course by Wed

 

 

Lesson 17: Simulation of Normally Distributed Data in Python

Review:

• Coin Flip simulation
• Dice simulation efforts

Presentation:

• Monte Carlo Simulation in Python
  • Discrete
    • Dice Simulation
  • Continuous
    • Normal Distribution Simulation
    • Stock Market Simulation

Activity:

• Use the parameters in Sheets “Annual” stock market simulation
• Write a program to simulate stock market returns for 1 40-year time frame.
• Edit the program to simulate stock market returns for 100 40-year time frames.
• Edit the program to simulate stock market returns for 10,000 40-year time frames.
• Save a screen capture to your portfolio

Assignment:

• Follow this link to join my DataCamp classroom
• Complete Intro to Python, Chapter 1, Python Basics
• Due before class on Monday