The expectation or expected value of a random variable is a single number that tells you a lot about the behavior of the variable. Roughly, the expectation is the average value, where each value is weighted according to the probability that it comes up. Formally, the expected value of a random variable r defined on a sample space s is: (B)=∑R()Pr(o) To appreciate its signficance, suppose S is the set of students in a class, and we select a student uniformly at random. Let r be the selected student's exam score. Then

Random variable Weve used probablity to model a variety of experiments, games, and tests. Through out, we have tried to compute probabilities of events. We asked for example, what is the probability of the event that you win the Monty Hall game? What is the probability of the event that it rains

1 Independent Events Suppose that we flip two fair coins simultaneously on opposite sides of room. Intu- itively, the way one coin lands does not affect the way the other coin lands. The mathe- matical concept that captures this intuition is called independence. In particular, events A and B are independent if and only if:

Introduction to Probability Probability is the last topic in this course and perhaps the most important. Many Igorithms rely on randomization. Investigating their correctness and performance re- quires probability theory. Moreover, many aspects of computer systems, such as memory

Conditional Probability Suppose that we pick a random person in the world. Everyone has an equal chance of being selected. Let A be the event that the person is an MIT student, and let B be the event that the person lives in Cambridge. What are the probabilities of these events? Intuitively

Generating functions Generating functions are one of the most surprising, useful, and clever inventions in discrete math. Roughly speaking, generating functions transform problems about se- quences into problems about functions. This is great because weve got piles of mathe- matical machinery for manipulating functions. Thanks to generating functions, we can

Counting III Today we'll briefly review some facts you dervied in recitation on Friday and then turn to some applications of counting. 1 The Bookkeeper Rule In recitation you learned that the number of ways to rearrange the letters in the wore BOOKKEEPER is:

We realize everyone has been working pretty hard this term, and were considering Warding some prizes for truly exceptional coursework. Here are some possible categories Best Administrative Critique We asserted that the quiz was closed-book. On the cover

Sums, Approximations, and Asymptotics II Block Stacking How far can a stack of identical blocks overhang the end of a table without toppling over? Can a block be suspended entirely beyond the table's edge? Table Physics imposes some constraints on the arrangement of the blocks. In particular, the stack falls off the desk if its center of mass lies beyond the desk's edge. Moreover, the center of mass of the top k blocks must lie above the(k+1)-st block;

In this example, the domain is the set fa,b, c, d, el and the range is the set Y= (1, 2, 3, 4, 5/. Related elements are joined by an arrow. This relation is a function because every element on the left is related to exactly one element on the right. In graph-theoretic