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Lecture notes files.
| WEEK # |
TOPICS |
| 1 |
Set and Probability Theory (PDF)
Basics of Set Theory |
| 2 |
Random Variables, Probability Mass/Density Function, and Cumulative Distribution Function (Univariate Model) (PDF) |
| 3 |
Multiple Random Variables, Bivariate Distribution, Marginal Distribution, Conditional Distribution, Independence, Multivariate Distribution (Multivariate Model) (PDF) |
| 4 |
Expectation (Moments) (PDF) |
| 5 |
Review for Exam 1 |
| 6 |
Random Variable and Random Vector Transformations (Univariate and Multivariate Models) (PDF) |
| 7 |
Special Distributions (Discrete and Continuous) (PDF)
Graph Representation: Special Distributions (PDF) |
| 8 |
Review for Exam 2 |
| 9 |
Random Sample, Law of Large Numbers, Central Limit Theorem (PDF)
Simulations: Magnifying Glass (PDF)# |
| 10 |
Point Estimators and Point Estimation Methods (PDF)
An Overview (PDF) |
| 11 |
Interval Estimation and Confidence Intervals (PDF)
t-Student versus Standard Normal: A Graphical View (PDF)
The t-Distribution versus the Normal Distribution (Java Applet) |
| 12 |
Hypothesis Testing (PDF)
An Applied Review (PDF) |
| 13 |
Review for Exam 3 |