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What is probability?
What is probability?

...  Let P(I) denote the winning probability of the horse I  P(I) = 1 / ( +1) = B(I) / B  That is the proportion of the bet on the horse I is the winning probability of the ...
Certain, impossible, event, mutually exclusive, conditional, bias
Certain, impossible, event, mutually exclusive, conditional, bias

Describing Contingency tables
Describing Contingency tables

... We will study the relationship between X and Y while controlling for Z. This can be done by studying the relationship at fixed levels of Z. This is a single slice (two-way table) from a three-way table, called a partial table. The table obtained by summing the partial tables is called the marginal t ...
Number of times resulting in event Total number of times experiment
Number of times resulting in event Total number of times experiment

... Law of Large Numbers states that as an experiment is repeated many times the empirical probability will approach the theoretical probability. Properties of probability 1. The probability of an event that can never occur is 0. 2. The probability of an event that will always occur is 1. 3. The probabi ...
Log-linear modeling and missing data
Log-linear modeling and missing data

Class 16 Lecture - UCI Social Sciences
Class 16 Lecture - UCI Social Sciences

... association among variables. Which one should you use? • Yule’s Q and Phi require a 2x2 table • Larger ordered tables: use Gamma, Tau-c, Somer’s d • Ideally, report more than one to show that your findings are robust. ...
Oh Craps!
Oh Craps!

2.8 Probability and Odds
2.8 Probability and Odds

The probability of an event, expressed as P(event), is always a
The probability of an event, expressed as P(event), is always a

A Tale of Three Numbers
A Tale of Three Numbers

... their professors. This means both groups over-represent young Westerners. (“Sampling bias”) ...
15.4 – 15.6: probability
15.4 – 15.6: probability

36 Odds, Expected Value, and Conditional Probability
36 Odds, Expected Value, and Conditional Probability

... A cube has three red faces, two green faces, and one blue face. A game consists of rolling the cube twice. You pay $ 2 to play. If both faces are the same color, you are paid $ 5(that is you win $3). If not, you lose the $2 it costs to play. Will you win money in the long run? Let W denote the event ...
Section 11
Section 11

probability quiz review. Match the vocabulary word with its definition
probability quiz review. Match the vocabulary word with its definition

... 22. You roll a number cube two times. What is the probability that you roll an odd number on the first roll and then a 4 on the second roll? Independent; P = 1/12 ...
Chapter 2-6: Probability
Chapter 2-6: Probability

Probability Rules! (7.1)
Probability Rules! (7.1)

Document
Document

Chapter 1: Probability models and counting
Chapter 1: Probability models and counting

... 2. Decimal odds (common in Europe). Decimal odds are expressed by a number (always greater than 1) which express the amount the betting house will pay for a winning bet of $1. For example decimal odds of 6 means that for a winning bet of $10 the player will get $60 back for a profit of $50. That is ...
theoretical probability
theoretical probability

... The odds against a spinner landing on red are 2:3. What is the probability of the spinner landing on red? The odds against landing on red are 2:3, so the odds in favor are 3:2. This means there are 3 favorable outcomes and 2 unfavorable outcomes for a total of 5 possible outcomes. ...
Chapter 3 Probability
Chapter 3 Probability

Algebra 1 - Davidsen Middle School
Algebra 1 - Davidsen Middle School

Basic Terms of Probability
Basic Terms of Probability

... • In words this says, that the odds of event E happening are number of times E happens divided by the number of times E does not happen. • Think success compared with failure. • Note odds use : , think of this as a fraction symbol or division sign. ...
Algebra 1 - Comments on
Algebra 1 - Comments on

B - IDA
B - IDA

... If any event is assigned a probability, that probability must satisfy the axioms. Example: Coin tossing Suppose you toss a coin. One possible event is “heads”, another is “tails” If you assign a probability p to “heads” and a probability q to “tails they both must be between 0 and 1. As “heads” cann ...
HCC MATH 1342 Spring 2014[1]. - HCC Learning Web
HCC MATH 1342 Spring 2014[1]. - HCC Learning Web

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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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