Week  Date  Topic  Reading  Note 
1  2/20  Course Introduction
Data: Type, Source, Applications, analysis
1. Traditional Data
 Elements, variables, and observations
 Data type
 Cross sectional and time series data
 Data sources
2. Descriptive Statistics: Single variable
 Frequency distributions
 Bargraphs, piecharts, histogram, etc.
 Measures of central tendency
 Measure of dispersion
 Chapters 13  Lab session 
2  2/27  3. Descriptive Statistics: Two variables
 Scatter plot
 Covariance and correlation
 Crosstabulation and scatter plots
Probability Distributions
 Normal distribution
 Standard normal distribution
 tdistribution
 c^{2} distribution
 F distribution
 Chapters 13
Chapter 6: sections 6.2  
3  3/5  Statistical Inference: Hypothesis Testing
 Basic concepts and procedure
 Types I and II errors
 Sampling distribution
 Single population/process hypothesis testing
 pvalue
 Chapter 8: sections 8.2, 8.3, 8.4
Chapter 9:
sections 9.4, 9.5  
4  3/12  Statistical Inference: Estimation
 Sampling methods
 Point and interval estimation
 Sample size selection
 Chapter 7: sections 7.2, 7.3, 7.4, 7.5, 7.6, 7.8  
5  3/19  Comparisons of Multiple Populations: Two Populations
 Paired samples
 Independent samples
 Chapter 10:
Sections 10.2, 10.3, 10.4  
6  3/26  Comparisons of Multiple Populations: ANOVA
 Partition of the sum of squares
 Oneway analysis of variance
 Multiple comparisons
 Chapter 13: sections 13.1, 13.2, 13.3, 13.5  
 4/2  Holiday   
7  4/9  Predictive modeling: Regression
 Basic concept
 Leastsquares estimation
 R^{2}
 Hypothesis testing
 Residual analysis
 Partition of the sum of squares
 Partial Ftest and ttest
 Indicator (Dummy) variables
 Build a regression model
 Chapters 14, 15, 16  
8  4/16  Regression Analysis (continued)
Predictive modeling: Classification
 Logistic regression
 Classification tree

Chapter 13: sections 13.1, 13.2, Handouts  
9  4/23  Classification (continued)  Handouts  
10  4/30  Midterm Exam   
11  5/7  Process and bottleneck analysis
 Overview of a process
 Throughput and bottleneck
 Resource capacity and Process capacity
 Inventory and waiting time
 Face game
 Reference:
Chapters 34  
12  5/14  Process and bottleneck analysis
 Capacity planning
 Analysis of Kristen Cookie
 Little’s Law
 M/M/1 queue
 M/M/N queue
 Reference:
Chapters 5
Case assignment: Kristen Cookie  
13  5/21  Linear Programming
 Problem formation
 Excel solver
 Sensitivity analysis
 Scheduling
 Portfolio analysis
  
14  5/28  Statistical process control
 Introduction to quality
 Control chart concepts
 chart
 R chart
 p and np chart
 Lean operations
 Chapter 19: 19.1, 19.2  
15  6/4  Epilogue and Final Exam   