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Course Content

We will cover the following material from the book;

Finite Mathematics and its Applications, 9th Edition, Goldstein, Schneider and Siegal.

We will also use the supplementary Course Packet.

(The course packet will be available starting Jan. 14 at 131 Decio (1st Floor),

through DCL Services. )

Chapter 5. Sets and Counting (Sections 5.1- 5.6, topics from 5.7).
Chapter 6: Probability (6.1-6.6)
Chapter 7: Probability and Statistics (7.1, 7.2, 7.4-7.6)
Chapter1: Very briefly (1.1-1.3)
Chapter 2: Matrices (2.1, 2.3, 2.4)
Chapter 3: Linear Programming (3.1, 3.2)
Chapter 9. Game theory (9.1-9.3)


Chapters 5, 6 and 7 deal with counting, probability and elementary statistics. This starts with an exposition of some useful and efficient techniques of counting. Next we apply these techniques to the calculation of probabilities or the chances of various events occurring. Statistical inference is the final topic, where we make inferences about probabilities on the basis of calculations on a sample taken from the population of interest.

Chapter 1 is mostly a review of results about lines. In Chapter 2 we examine systems of linear equations and their solutions. Matrices are introduced and we see how these can be used to solve systems of linear equations.

In Chapter 3 we deal with optimization problems. An example might be if you wanted you maximize your scores for this course, but had a constraint on the amount of time available to spend on the course. You would then, of course, have to pick and choose in order to use your time to your best advantage. Sometimes such problems can be reduced to graphing some lines and solving systems of equations. This is the content of
Chapter 3.

In Chapter 9, we look at game theory i.e. the mathematics of strategy. If you play a game, you want to maximize your returns, or minimize your losses as the case may be, i.e. you want to play an optimal strategy. We use matrix theory, the theory from chapter 3 and a little probability to find this optimal strategy.