ECE 313 Powerpoint Slides by Professor D.V. Sarwate

Spring 2012

These Powerpoint slides were used in videotaping the course in Fall 2000. They are being made available as "handouts" consisting of six-slides-to-a-page printable .pdf files. Click here if you would like to view the original slides in color and with full animation.

• 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

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Prof. Hutchinson's slides

• Lecture #29: Conditional Distributions

• Lecture #30: Jointly Distributed Random Variables

• Lecture #31: Jointly Continuous Random Variables

• Lecture #32: Functions of Multiple Random Variables

• Lecture #33: Independent Random Variables

• Lecture #34: Functions of Independent Random Variables

• Lecture #35: Multiple Functions of Multiple Random Variables

• Lecture #36: Expectation

• Lecture #37: Jointly Gaussian Random Variables

• Lecture #38: Conditional Distributions

• Lecture #39: Conditional Expectation

• Lecture #40: Limit Theorems I

• Lecture #41: Limit Theorems II