George Mason University
Volgenau School of Engineering
Department of Statistics

STAT 346: Probability for Engineers

Sec. 002

Fall Semester, 2019
Thursdays from 7:20 to 10:00 PM (starting August 29, with other dates given below)

Location: room 2003 of Art and Design Building


Instructor: Clifton D. Sutton


Text:

Fundamentals of Probability with Stochastic Processes, 4th Ed., by Ghahramani (CRC Press, 2019)


Prerequisite:

MATH 213 or MATH 215 (i.e., three semesters of calculus) with a grade of C or better


Description:

This course covers elementary probability. After covering the axioms of probability and some of their consequences, the course covers simple combinatorics, conditional probability, independence, random variables, common discrete and continuous distributions, joint distributions, expectation, limit theorems, and assorted other topics.

Objectives / Learning Goals:

The objectives of this course are (1) to help students learn the basics of probability, and (2) teach students how to apply them to solve a wide variety of problems. Homework and exams problems will be used to measure how well students master the material. The focus will be on problem solving and calculations as opposed to theory and proofs.

Approximate week-by-week content:

[1] Aug. 29:
axioms of probability and some results which follow from them
[Ch. 1 of text (skipping Sec. 1.5 and Example 1.22);
I'll cover this Exercise/Problem from the text: 23 (p. 24)]
[2] Sep. 5:
combinatorics
[Ch. 2 of text;
I'll cover these Exercises/Problems from the text: 9 (p. 73), 23 (p. 74), & parts of 35 (p. 75) (and I'll also cover Examples 2.8, 2.9, and the first part of 2.22)]
[3] Sep. 12:
conditional probability
[Sec. 3.1 through Sec. 3.4 of text, and part of Sec. 3.5;
I'll cover these Exercises/Problems from the text: 32 (p. 84) & 10 (p. 99) (and I'll also cover Example 3.7 (p. 91))]
[4] Sep. 19:
independence; introduction to random variables
[Section 3.5 of text, and Sections 4.1 through 4.3 of text;
I'll cover these Exercises/Problems from the text: 37 (p. 134), 5 (p. 155), 1 (p. 190), & 9 (p. 191)]
[5] Sep. 26:
discrete random variables (expectation and other moments)
[Sec. 4.4 through Sec. 4.6 of text (skipping Examples 4.21 and 4.22) and Sec. 5.1 of text;
I'll cover these Exercises/Problems from the text: 2 & 4 (p. 175), 14 (p. 177), 6(b) (p. 185), 9 (p. 185), 5 (p. 190), & 23 (p. 205) (and I'll also cover Example 4.18 (p. 168)]
[6] Oct. 3:
special discrete distributions
[Ch. 5 of text;
I'll cover these Exercises/Problems from the text: 1 (p. 218), 12 (p. 219), 20 (p. 220), 12 (p. 234), 7 (p. 238)]
[7] Oct. 10:
continuous random variables (lecture during 1st half of class)
[Sec. 6.1 and part of Sec. 6.2 of text;
I'll cover these Exercises/Problems from the text: 2 (pp. 249-250), 5 (p. 250), 1 (p. 257), parts of 6 (p. 274)]
Exam 1* (on Ch. 1 through Ch. 3 (2nd half of class period, closed book and notes))
[8] Oct. 17:
moments of continuous random variables; some special continuous distributions
[Sec. 6.2, Sec. 6.3, Sec. 7.1 and part of Sec. 7.2;
I'll cover this Exercise/Problem from the text: parts of 6 (p. 274)]
[9] Oct. 24:
more special continuous distributions, introduction to joint distributions
[Sections 7.2, 7.3, 7.4, & Sec. 7.6 of text (with Sec. 7.5 being skipped), and just a little of Sec. 8.1;
I'll cover these Exercises/Problems from the text: 2 (p. 295), 6 (p. 295), 1 & 5 (p. 303), 12 (p. 304), 3 & 6 (p. 310), 5 (pp. 321-322), 1 (p. 342)]
[10] Oct. 31:
bivariate distributions, independent random variables
[Sec. 8.1 and 8.2 of text;
I'll cover these Exercises/Problems from the text: part of 4 (p. 343), part of 11(a) (p. 344), 12 (p. 357)]
[11] Nov. 7:
conditional distributions, joint distributions for more than two random variables
[Sec. 8.3 (with most of (but not all of) Sec. 8.4 being skipped) and Ch. 9 of text (with some portions of Ch. 9 being skipped);
I'll cover these Exercises/Problems from the text: 1 (p. 371), 8 (p. 372), parts of 3 (p. 407), 9 (p. 408), 4 (p. 416)]
[12] Nov. 14:
expectation for sums of random variables, covariance (lecture during first half of class)
[Sec. 10.1 and part of Sec. 10.2 of text;
I'll cover these Exercises/Problems from the text: 3, 5, & 6 (p. 436), 1 (p. 450)]
Exam 2* (on Ch. 4 through Ch. 7 (2nd half of class period, open book and notes))
[13] Nov. 21:
correlation; moment generating functions
[Sec. 10.2 and 10.3 of text (with Sections 10.4 and 10.5 being skipped); also Sec. 11.1 of text;
I'll cover these Exercises/Problems from the text: 9 (p. 491), 18(b) & 21 (p. 492) (and I'll also cover Example 10.17 (p. 453))]
[**] Nov. 28:
no class due to Thanksgiving Day
[14] Dec. 5:
sums of independent random varaibles, some inequalities and limit theorems
[Sections 11.2, 11.3, 11.4, and 11.5 (with Example 11.32 being skipped) of text;
I'll cover these Exercises/Problems from the text: 9(b) (p. 499), 1 & 9 (p. 527), 8 (p. 532)]
[**] Dec. 12:
Final Exam* (note: exam period is from 7:30 to 10:15 PM)
*Note: While it's fairly well fixed that the midterm exams will be during the 7th and 12th class meetings, the dates may be changed if any classes are cancelled due to bad weather (or for any other reason). Also, be aware that the Provost may change the final exam schedule if there are problems with class cancellation during the semester.


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