ECE 313 Study Guide - Midterm Guide: Gamma Distribution, Geometric Distribution, Central Limit Theorem

• School: University of Illinois
• Department: Electrical and Computer Engineering
• Course: ECE 313
• Professor: Y Lu

Document Summary

Exam 2 covers problems, lectures, and reading up until (and including) section 4. 4 , with emphasis on sections 3. 1 through 4. 4. You should know the meanings, forms, means, and variances for the key continuous-type distributions for exam 2 (see the inside back cover of the course notes). * cumulative distribution functions (ch 3. 1) [saq 3. 1] * probability density functions (ch 3. 2) [saq 3. 2] [simplepdf] * gaussian (normal) distribution (e. g. using q and phi functions) (ch. * the central limit theorem and gaussian approximation (ch. * ml parameter estimation for continuous type random variables (ch. * the distribution of a function of a random variable (ch 3. 8. 1) [saq 3. 8] * generating random variables with a specified distribution (ch 3. 8. 2) * failure rate functions (ch 3. 9) [saq 3. 9] * binary hypothesis testing for continuous type random variables (ch 3. 10) [saq 3. 10] * joint pdfs of independent random variables (ch 4. 4) [saq 4. 4]