Lectures	Sections in Text	Brief Description
6/23	1.1	Numbers
6/25	1.2, 1.3	Equations and Inequalities; Sums
6/26 (x-hour)	1.4, 1.5	Elements of Set Theory; Venn Diagrams
6/27	1.6	Averages
6/30	2.1	Basic Counting Principles
7/2	2.2, 2.3	Arrangements; Selections
7/3 (x-hour)	2.4	More About Selections
7/7	3.1, 3.2	Events; Probability Measures
7/9	3.3	Non-Uniform Probabilities
7/10 (x-hour)	3.4	Counting and Probability
7/11		Midterm I
7/14		Introduction to Graph Theory: Guest Lecture
7/16		Introduction to Graph Theory: Guest Lecture
7/18		Introduction to Graph Theory: Guest Lecture
7/21	3.5, 3.6	Stochastic Processes; More About Conditional Probability
7/23	3.7, 3.8	Bayes' Formula and Applications; Further Examples of Bayes' Formula
7/25	3.9	Expected Values
7/28		More About Graph Theory
7/30		More About Graph Theory
7/31 (x-hour)		More About Graph Theory
8/1		Midterm II
8/4	5.1, 5.2	Coordinates, Lines; Systems of Linear Equations
8/6	5.3	Formal Solution of Systems of Equations
8/8	5.4	Matrices and Vectors
8/11	5.5	Vector and Matrix Products
8/13	5.6	Inverses
8/15	5.7	More About Inverses
8/18		Introduction to Number Theory
8/20		Introduction to Number Theory
8/24		Final Exam, 11:30 am

Mitsuo Kobayashi