STA 371G

Basic Information

• Instructor: Mingyuan Zhou
  
• Office: CBA 6.462
• Email: mingyuan.zhou@mccombs.utexas.edu
• Phone: 512-232-6763
• Office Hours: Tuesday Thursday 3:30-4:30 PM. Welcome to come by my office at other times as well.
• Teaching Assistants:
  • Xiao Han, xiao dot han at phd.mccombs.utexas.edu
  • Office Hours: Monday, 2:00-3:00 PM, CBA 4.304A-"D"
  • Long Zhao, long dot zhao at phd.mccombs.utexas.edu
  • Office Hours: Friday, 10:00-11:00 AM, CBA 4.304A-"D"

Syllabus

syllabus_STA371G.pdf

Outline (Day by Day)

outline_STA371G.pdf

Class Notes

• Review of Basic Probability and Statistics
  • 1.1 Random Variables and Probability Distributions
            Jan14_ClassEnrollment.R, Jan14_NameLength.R
    
  • 1.2 Normal and Binomial Distributions
            PlotNormal.xlsx, TestScore.xlsx, plotNormal.R
    
  • 1.3 Estimation and Sampling Distributions
            SamplingDist.R, StudentT.R
    
• Simple Linear Regression
  • 2.1 Least Squares Estimation
            House_SLR.xls, House_SLR.R, BaseBall_SLR.xls, BaseBall_SLR.R, RunsPerGame.txt
    
  • 2.2 Covariance and Correlation, Goodness of Fit
            House_Corr.xls, House_Corr.R
    
  • 2.3 Model Assumptions
            Stock.xls
    
  • 2.4 Sampling Distributions and Confidence Intervals for Regression Parameters
• Multiple Linear Regression
• 3.1 Multiple Linear Regression
          AutoMPG_MLR.xls, AutoMPG_MLR.R, ScatterPlotAuto.pdf                   Baseball_MLR.xls, Baseball_MLR.R, ScatterPlotBaseball.pdf        Supervisor_MLR.xls,   NBeer_MLR.xls
  
• 3.2 Dummy Variables and Interactions
          BankSalary.xls, BankSalary.R, SalaryData.txt                                     MidCity.xls, MidCity.R, MidCity.txt
  
• 3.3 Diagnostics and Transformations
          Anscombe.xls, Anscombe.R                                                                         Telemarketing.xls, Telemarketing.R, Telemarketing.txt                                     GPA.xls                                                                                                           MPG_Auto_Log.R                                                                                                           OrangeJuiceSale.xls, OrangeJuiceSale.R, OrangeJuiceSale.txt
  
• Time Series
• 4.1 Fitting a Trend
• 4.2 Autoregressive Models
          Stock Closing Prices
  
• 4.2 Modeling Seasonality
• Model Selection
• 5 Model Selection
• Decision Making
• 6.1 Probability, Betting Odds and Bayes' Theorem
• 6.2 Decision Criteria and Utility Functions
• 6.3 Decision Trees
• 6.4 The Value of Information
• Simulation
• 7.1 Introduction to Monte Carlo Simulation
          Market_Simulation_imcomplete.xls, Market_Simulation.xls, RollaDie.R, Roll2Dice.R,         Simulate_Pi.xls, Simulate_Pi.R,         Simulation.R
  
• 7.2 Introduction to Monte Carlo Simulation: Examples
          Simulation2.R
  

Homework

• Homework Assignment 1, Solution, Due in Class on Thursday, 01/23/2014 (can also be uploaded to Canvas)
• Homework Assignment 2, Solution, Due in Class on Tuesday, 02/04/2014
• Homework Assignment 3, Solution, Amore.R, Due in Class 11:59 PM on Tuesday, 02/11/2014
• Homework Assignment 4, Solution, Due in Class on Thursday, 02/20/2014
           Price and Sales, Waite First Securities, Milk and Money
  
• Homework Assignment 5, Solution, Due in Class on Thursday, 03/20/2014
           Profits.csv, RunsPerGame.csv, zagat.csv, Orion Bus Industries
  
• Homework Assignment 6, Solution, Due in Class on Thursday, 03/27/2014
           MidCity.csv, Profits.csv, AutoMPG.csv, Oakland_A.xls, Oakland_B.xls
  
• Homework Assignment 7, Solution, Solution_Excel, Due in Class on Thursday, 04/03/2014
           Northern Napa Valley Winery
  
• Homework Assignment 8, Solution, Due in Class on Thursday, 04/24/2014 9:00 PM on Friday, 02/25/2014

Topic Summaries

• Practice Exam #1, Solution
• Topic Summary for Exam #1
• Topic Summary for Exam #2
• Topic Summary for the Final Exam
• Practice questions for the final exam are posted in Canvas/Files