` DATA ANALYSIS AND DECISION MAKING

DATA ANALYSIS AND DECISION MAKING 22:960:575

Instructor: Prof. Michael N. Katehakis, Ph.D.

TA:
TBA ,      send email

Syllabus       Academic-Calendar      

    Note: Mid Term on March 30
(No class on March 23)

    A nice free Introduction to Probabilty text: E. S. Wentzel: Probability Theory (First Steps)

Notes and Assignments

Lectures Class Notes and Exampless Assignments & Solutions
  1   a)   Random Variables
  b)   Simulation: Example 1  
  c)   Simulation: Example 2
    a) READ: Chapters 1, 2
      of Introduction to Probability,
    b) READ: Chapters 1, 2, 5
        of Main Text:
  2   a)   Simulation: Data-Table
  b)   Simulation: more applications
  c)   Simulation: with Mathematica
  a) READ: Chapter 2, pp.49-82
  b) READ: Chapter 3, pp. 111-132
  c) READ: Chapter 5, pp. 195-219
  3   a)   Lecture Notes
  b)   Joint Distributions - correlation
  a)   Do Problems 2.23, 2.24, 2.26 p. 106-107
        Prepare     Solutions
  4   a)   Simulation: Data-Table
  b)   Simulation: Inventory Control
  c)   Introduction to : Estimation
  5   a)   Class Example: Histograms for Coins
  b)   Class Example 2: Inventory and 401K Simulation
  a)   Solve Problem in `Finance Simulation' Sheet of Inventory and 401K Simulation   Prepare
  b)   Study the excel files posted
  c)   Read Sections 3.1 - 3.8 of Chapter 3.
  6   a)   Problem in `Finance Simulation' Solution
  b)   Data Tables with Two Variables
  a)   Study the excel files posted
  7   a)   Bayes Estimation
      (review Section 2.12 of text)
  b)    Continuous Distributions and C.L.T. - xlsx    
  c)    Confidence Intervals - xlsx
  d)    Theory Insight
  a)   Study the excel files posted
  b)   Read Sections 4.1 - 4.4 of Chapter 4.
  c)   Study the Case Study of sec 4.11
  d)   Solve Problems 4.1, 4.2, 4.3 and 4.11 of Chapter 4.
        Solutions
    Bayes Problem Collect with email
   Solution by Ms. Josephine Bagtas
  8   a)   CLT Bernoulli random variables
  b)   CLT Uniform random variables
  c)   Confidence Intervals - mean difference
  d)   Confidence Intervals - proportions
  a)   Solve Problems 4.18, 4.19, 4.20
  Solutions

  b)   Confidence Intervals - theory
  9   a)   CI for the Variance of Normals
  b)   Tests of Hypothesis    
  a)   Read:   Hypothesis Tests
  b)   Watch: Hypothesis Tests #1 and Hypothesis Tests #2
      Project      
  10   Regression       Study examples of regression2.xlsx
    Read sections 6.1-6.3 and do problems 6.1 & 6.3 p. 315, to be collected  
  11   Moving-Average & Exp-Smoothing
  Study solutions of problems 6.1, 6.3  

    Do problems 6.7 & 6.8 p. 321.   Due on Apr. 27
  12   Optimal Assignment
  Binary Optimization
  Read Sec 9.1-9.3.
  13   Study Project Solution
  Study QR-Model
  Do problems 9.1, 9.3, 9.5. Due on May 4.
  Solve the QR-Model posted, when the lead time is 5 days. Due on May 4.
  14   Introduction to Linear Optimization
  Decision Theory
  Review
    Problems from Chapter 4
    Problems from Chapters 7 & 9







Links of Interest

EXCEL: Windows Excel Shortcuts Mac Excel Shortcuts Excel Tutorial video
Learn R: R tutorial Download and Install R Download and Install RStudio
Learn Python: Python Software Foundation Python Tutorial for Beginners 1: Install and Setup for Mac and Windows Download and Install Pyzo
Learn Mathematica: Mathematica tutorial Download and Install Mathematica   *   Mathematica on Raspberry Pi
  *   Video for Mathematica on Raspberry Pi
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