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Feb 23 (Lecture 3)
Feb 23 (Lecture 3)

... Solution: Let E = {(H,H)} be the event that both flips land heads, and F={(H,H), (H,T)} denote the event that the first flip lands heads, then the desired probability is given by P( E | F )  ...
Laws of Probability
Laws of Probability

... While giving the basic rules governing probability, we have said nothing about how to assign probabilities other than to say that any such assignment should be consistent with the laws of probability! In practice, we assign probabilities based on information about events that has already been gather ...
Check your answers
Check your answers

...  Are repeating a grade and having social problems independent or correlated? If correlated, describe how they are correlated. Those who have repeated a grade are more likely to have social problems than those who have not repeated a grade.  Among those who have repeated a grade, what are the odds ...
Introduction to Probability Exercise sheet 3 Exercise 1. 5 cards
Introduction to Probability Exercise sheet 3 Exercise 1. 5 cards

union
union

... • The probability of 2 people having the same birthday in a room of 41 people is 90%. • To randomly select ___ birthdays, randInt (1, 365, __)L1:SortA(L1) This will sort the day in increasing order; scroll through the list to see duplicate birthdays. Repeat many times. • The following short program ...
Grade D Probability
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... says if you get it right she will release you from “the game” for the night. But if you are wrong, she will put you one step closer to being stuck forever in . . . ...
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6.3 Notes

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Probability Review

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... – But also: winning a race, getting a ‘tail’ result when flipping a coin, encountering a certain word ...
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...  The mean is an important indicator of quality  The standard deviation is just as important  Quality control to ensure minimum spread in properties  Economic penalty of a ‘broad’ distribution  “derating” to ‘guarantee’ a value ...
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PROBABILITY, Problems to Lesson 2. 1. Matching problem
PROBABILITY, Problems to Lesson 2. 1. Matching problem

... • There is one secretarial position available. • The number n of applicants is known. • The applicants are interviewed sequentially in random order, each order being equally likely. • It is assumed that you can rank all the applicants from best to worst without ties. The decision to accept or reject ...
Notes on Probability
Notes on Probability

... Example: let A be the event of getting an even number when rolling a fair die. Three outcomes correspond to this event, namely 2, 4 and 6, ...
Section 6.2 ~ Basics of Probability Objective: After this section you
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Binomial Distributions

... Have a fixed number of trials  Each trial has tow possible outcomes  The trials are independent  The probability of each outcome is constant ...
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00i_GEOCRMC13_890522.indd

... Determine whether the events are mutually exclusive or not mutually exclusive. Then find the probability. Round to the nearest hundredth. 1. SHELTER selecting a cat or dog at the animal shelter that has 15 cats, 25 dogs, 9 rabbits and 3 horses ...
PS3 PROBABILITY 9A: EXPERIMENTAL PROBABILITY
PS3 PROBABILITY 9A: EXPERIMENTAL PROBABILITY

12.4 Probability of Compound Events
12.4 Probability of Compound Events

... standard deck of 52 cards. Find the probability of the given event. ◦ The card is not a king. ◦ The card is not an ace or a jack. ...
Probability PowerPoint notes
Probability PowerPoint notes

... Lawrence is the captain of his track team. The team is deciding on a color and all eight members wrote their choice down on equal size cards. If Lawrence picks one card at random, what is the probability that he will pick blue? ...
Probability - TeacherWeb
Probability - TeacherWeb

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Lesson 12-8

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D6 Probability

Notes for Lesson 10-7: Independent and Dependent Events
Notes for Lesson 10-7: Independent and Dependent Events

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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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