STA 371G

Basic Information

• Instructor: Mingyuan Zhou, Ph.D., Associate Professor of Statistics
  
• Office: CBA 6.458 (Six floor, on the east side of the building that faces the entrance of Gregory Gym)
• Email: mingyuan.zhou@mccombs.utexas.edu
• Phone: 512-232-6763
• Website: http://mingyuanzhou.github.io/
• Office Hours: Monday & Wednesday 3:30-4:30 PM. Welcome to come by my office at other times as well.
• Teaching Assistant:
  • Quan Zhang, quan.zhang@mccombs.utexas.edu, IROM PhD Student, Office Hours: Tuesday, 1:00 to 2:30 pm, CBA 4.304A-C
• Midterm Exam: GEA 105, 6:45-9:45 pm, Monday, 10/21/2019
• Final Exam: ART 1.102, December 16, 7 to 10 pm

Syllabus

syllabus_STA371G_Fall2019.pdf

Outline (Day by Day, updated one day before each class)

outline_STA371G_2019.pdf

Learning R

https://github.com/jgscott/learnR

Class Notes

• Decision Making under Uncertainty
• 1.1 Random Variables and Probability Distributions
          Jan14_NameLength.R
  
• 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
• Normal Distribution, Estimation and Sampling Distribution, and Introduction to Simulation
• 1.2 Normal and Binomial Distributions
  Lecture note 3 / Lecture note 4
          PlotNormal.xlsx, TestScore.xlsx, plotNormal.R
  
• 1.3 Estimation and Sampling Distributions
          SamplingDist.R, StudentT.R
  
• 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
  
• 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
  
• 4.3 Modeling Seasonality
• Model Selection
• 5 Model Selection
• Simulation
• 7.2 Introduction to Monte Carlo Simulation: Examples
          Simulation2.R
  

Homework and Case Study (about nine in total)

• Homework Assignment 1, Solution, Due in Class on Wednesday, 09/11/2019
• Homework Assignment 2, Solution, Due in Class on Monday, 09/23/2019
• Homework Assignment 3, Solution, Due in Class on Monday, 09/30/2019
• Homework Assignment 4, Solution, Due in Class on Monday, 10/07/2019
• Homework Assignment 5, Solution, Amore.R, Due in Class on Wednesday, 10/09/2019
• Homework Assignment 6, Case file, Solution, Due in Class on Wednesday, 10/16/2019
• Homework Assignment 7, Solution, Due in Class on Wednesday, 11/06/2019,
           Price and Sales, Waite First Securities, Milk and Money
  
• Homework Assignment 8, Solution, Due in Class on Wednesday, 11/20/2019
           Profits.csv, RunsPerGame.csv, zagat.csv, Orion Bus Industries
  
• Homework Assignment 9, Solution, Due in Class on Monday, 12/2/2019
           MidCity.csv, Profits.csv, AutoMPG.csv, Oakland_A.xls, Oakland_B.xls
  
• Homework Assignment 10, Solution, Solution_Excel, Due in Class on Monday, 12/9/2019
           Northern Napa Valley Winery
  

Topic Summaries

• Topic Summary for Midterm Exam
• Topic Summary for the Final Exam
• Practice tests for the Final Exam can be found in Canvas/files