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Topic #5: Probability
Topic #5: Probability

Ch16 Review
Ch16 Review

IGE104-Lecture9
IGE104-Lecture9

Randomness and Probability
Randomness and Probability

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Empirical Probability

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PDF

Chapter 10 Idea of Probability Probability Model for Two Dice
Chapter 10 Idea of Probability Probability Model for Two Dice

... some outcome must occur on every trial, the sum of the probabilities for all possible outcomes must be exactly one. ...
Ch6 Probability Review Name: Government data give the following
Ch6 Probability Review Name: Government data give the following

... was accidental, is? 3. The conditional probability that the death was accidental, given that the victim was male, is? 4. Let A be the event that a victim of violent death was a woman and B the event that the death was a suicide. The proportion of suicide among violent deaths of women is expressed in ...
Chapter 10
Chapter 10

... Random phenomenon: roll pair of fair dice and count the number of pips on the up-faces. Find the probability of rolling a 5. ...
Lecture 3. Combinatorial Constructions Many probability spaces
Lecture 3. Combinatorial Constructions Many probability spaces

... latter is much easier than the former. Similarly, if A is an event, then it may be much easier to compute the probability that A does not occur than to compute the directly the probability that it does. But the former determines the latter. Problem. The letters of “M ISSISSIP P I” are scrambled. Wha ...
13. A psychologist determined that the number of sessions required
13. A psychologist determined that the number of sessions required

... c. Make some comparisons between the number of laptops and the number of desktops owned by the Journal’s subscribers. 23. a. Laptop: E (x) = .47(0) + .45(1) + .06(2) + .02(3) = .63 Desktop: E (x) = .06(0) + .56(1) + .28(2) + .10(3) = 1.42 b. Laptop: Var (x) = .47(-.63)2 + .45(.37)2 + .06(1.37)2 + .0 ...
2.4 Bernoulli Trials/Binomial Experiments
2.4 Bernoulli Trials/Binomial Experiments

Ch5 Study Questions File
Ch5 Study Questions File

Lecture Note 7
Lecture Note 7

... Ex. A store sells 2 different brands of DVD players. Of its DVD player sales, 60% are brand A (less expensive) and 40% are brand B. Each manufacturer offers a 1-yr warranty on parts and labor. It is known that 25% of brand A’s DVD players require warranty repair work, whereas 10% for brand B. (a) W ...
Lesson 12-4: Multiplying Probabilities
Lesson 12-4: Multiplying Probabilities

ORMS 3310 - Chapter 4 Practice Problems 1. Suppose that, from a
ORMS 3310 - Chapter 4 Practice Problems 1. Suppose that, from a

... Suppose that, from a population of 50 bank accounts, we want to take a random sample of 4 accounts in order to learn about the population. How many different random samples of 4 accounts are possible? ANSWER: 230,300 ...
COMP245: Probability and Statistics 2016
COMP245: Probability and Statistics 2016

Probability
Probability

... An experiment is any process of observation with an uncertain outcome. The possible outcomes for an experiment are called the experimental outcomes. Probability is a measure of the chance that an experimental outcome will occur when an experiment is carried out ...
Probability bingo
Probability bingo

... of solving a problem by conducting an experiment that is similar to the situation in the problem. EXAMPLE: You flip a coin to predict if a baby will be a boy or a girl. ...
Gain Confidence with Probability: The Two-Way Table 1
Gain Confidence with Probability: The Two-Way Table 1

COMP 245 Statistics Exercises 2
COMP 245 Statistics Exercises 2

5.3 Conditional Probability, Dependent Events, Multiplication Rule
5.3 Conditional Probability, Dependent Events, Multiplication Rule

... Statistics Notes:  5.3 Conditional Probability, Dependent Events, Multiplication Rule 5.3  Conditional Probability and the Multiplication Rule Two members from a 5­member committee are to be randomly selected to serve as  chairperson and secretary. The 1st person selected will be the chair and the 2 ...
A Survey of Probability Concepts
A Survey of Probability Concepts

... Sum of Classical Probabilities If a set of events is mutually exclusive and collectively exhaustive, then the sum of the probabilities is 1.  Mutually exclusive: occurrence of one event means that none of the other events can occur at the same time.  Collectively exhaustive: at least one of the e ...
11-2 Basic Probability
11-2 Basic Probability

2.2 Let E and F be two events for which one knows that the
2.2 Let E and F be two events for which one knows that the

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Odds

Odds are a numerical expression, always consisting of a pair of numbers, used in both gambling and statistics. In statistics, odds for reflect the likelihood that a particular event will take place. Odds against reflect the likelihood that a particular event will not take place. The usages of the term among statisticians and probabilists on the one hand, versus in the gambling world on the other hand, are not consistent with each other (with the exception of horse racing). Conventionally, gambling odds are expressed in the form ""X to Y"", where X and Y are numbers, and it is implied that the odds are odds against the event on which the gambler is considering wagering. In both gambling and statistics, the 'odds' are a numerical expression of how likely some possible future event is.In gambling, odds represent the ratio between the amounts staked by parties to a wager or bet. Thus, odds of 6 to 1 mean the first party (normally a bookmaker) is staking six times the amount that the second party is. Thus, gambling odds of '6 to 1' mean that there are six possible outcomes in which the event will not take place to every one where it will. In other words, the probability that X will not happen is six times the probability that it will.In statistics, the odds for an event E are defined as a simple function of the probability of that possible event E. One drawback of expressing the uncertainty of this possible event as odds for is that to regain the probability requires a calculation. The natural way to interpret odds for (without calculating anything) is as the ratio of events to non-events in the long run. A simple example is that the (statistical) odds for rolling six with a fair die (one of a pair of dice) are 1 to 5. This is because, if one rolls the die many times, and keeps a tally of the results, one expects 1 six event for every 5 times the die does not show six. For example, if we roll the fair die 600 times, we would very much expect something in the neighborhood of 100 sixes, and 500 of the other five possible outcomes. That is a ratio of 100 to 500, or simply 1 to 5. To express the (statistical) odds against, the order of the pair is reversed. Hence the odds against rolling a six with a fair die are 5 to 1. The probability of rolling a six with a fair die is the single number 1/6 or approximately 16.7%.The gambling and statistical uses of odds are closely interlinked. If a bet is a fair one, as in a wager between friends, then the odds offered to the gamblers will perfectly reflect relative probabilities. A fair bet that a fair die will roll a six will pay the gambler $5 for a $1 wager (and return the bettor his or her wager) in the case of a six and nothing in any other case. The terms of the bet are fair, because on average, five rolls result in something other than a six, at a cost of $5, for every roll that results in a six and a net payout of $5. The profit and the expense exactly offset one another and so there is no disadvantage to gambling over the long run. If the odds being offered to the gamblers do not correspond to probability in this way then one of the parties to the bet has an advantage over the other. Casinos, for example, offer odds that place themselves at an advantage, which is how they guarantee themselves a profit and survive as businesses. The fairness of a particular gamble is more clear in a game involving relatively pure chance, such as the ping-pong ball method used in state lotteries in the United States. It is much harder to judge the fairness of the odds offered in a wager on a sporting event such as a football match.
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