ECE 313 Powerpoint Slides

Fall 2003

These Powerpoint slides, in "handout" form consisting of six-slides-to-a-page printable .pdf files, were used in teaching a web-based version of ECE 313 in Fall 2000.

• Lecture #00: What is this course all about? An introduction to ECE 313 for off-campus students

• Lecture #01: Introduction to ECE 313

• Lecture #02: The Probability Model

• Lecture #03: The Axioms of Probability, Part I

• Lecture #04: The Axioms of Probability, Part II

• Lecture #05: The Axioms of Probability, Part III

• Lecture #06: Random Variables

• Lecture #07: Mean, LOTUS, and Variance

• Lecture #08: Independent Trials

• Lecture #09: Statistical Estimation

• Lecture #10: Confidence Intervals

• Lecture #11: Important Counting Random Variables

• Lecture #12: Conditional Probability

• Lecture #13: The Theorem of Total Probability

• Lecture #14: Bayes' Formula

• Lecture #15: Decision-making under uncertainty I

• Lecture #16: Decision-making under uncertainty II

• Lecture #17: Decision-making under uncertainty III

• Lecture #18: Independent Events

• Lecture #19: System Reliability I

• Lecture #20: System Reliability II

• Lecture #21: The Cumulative Distribution Function

• Lecture #22: Continuous Random Variables I

• Lecture #23: Continuous Random Variables II

• Lecture #24: Continuous Random Variables III

• Lecture #25: Poisson Random Processes

• Lecture #26: Gaussian Random Variables and two associated pictures of parts of a German bank note

• Lecture #27: Functions of Random Variables

• Lecture #28: Hazard Rates and System Reliability

• Lecture #29: Decision-making under uncertainty IV

• Lecture #30: Joint Distributions of Random Variables

• Lecture #31: Joint Probability Mass Functions

• Lecture #32: Jointly Continuous Random Variables I

• Lecture #33: Jointly Continuous Random Variables II

• Lecture #34: Jointly Continuous Random Variables III

• Lecture #35: Functions of Many Random Variables I

• Lecture #36: Functions of Many Random Variables II

• Lecture #37: Functions of Many Random Variables III

• Lecture #38: Expectation, Covariance, and Correlation

• Lecture #39: Jointly Gaussian Random Variables

• Lecture #40: Mean-Square Estimation

• Lecture #41: Limit Theorems