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Algebra 1 Summer Institute 2014 The Poker Manipulation Summary
Algebra 1 Summer Institute 2014 The Poker Manipulation Summary

Section 6-5 Sample Spaces and Probability
Section 6-5 Sample Spaces and Probability

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... A century ago, French treatises on the theory of probability were commonly called “Le Calcul des Probabilités”—“The Calculus of Probabilities.” The name has fallen out of fashion, perhaps due to the potential confusion with integral and differential calculus, but it seems particularly apt for our p ...
to access this booklet
to access this booklet

... How likely is this result if the coin was fair - that is the chance of it landing heads up is the same as the chance of it landing tails up? Probability allows us to give this likelihood a number . When writing about a survey or experiment it is important to explain what the chance is that the resul ...
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... A coin is flipped 4 times. What is the probability of flipping 4 heads in a row. Because each flip of the coin has an equal probability of landing heads up, or a tails, the sample space for each flip is the same. The events are independent. P(h, h, h, h) = P(h) • P(h) • P(h) • P(h) The probability o ...
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... that are supposed to give readings of zero degrees Celsius at freezing point of water. Tests on large sample of these instruments reveal that at the freezing point of water, some thermometers give readings below zero degrees and some above zero degrees. Assume that the mean reading is zero degrees C ...
Gunawardena, K.
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... problems of statistical inference including estimation and confidence intervals, test of hypothesis and regression. Prerequisite: 67-103 with a grade of C or better or placement Learning Objectives: Upon successful completion of this course, the student will be able to  use analytical skills to res ...
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... of [0, 1] that can be obtained from intervals by taking unions, intersections, and complements a finite or countably infinite number of times. A standard choice of probability measure here is the one that assigns [a, b] its length, P ([a, b]) = b − a. The probability of other sets in F is then uniqu ...
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... She should expect to lose 11 cents. Therefore, this is not a winning strategy. 21. A total of 4 buses carrying 148 students from the same school arrives at a football stadium. The buses carry, respectively, 40, 33, 25, and 50 students. One of the students is randomly selected. Let X denote the numbe ...
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... Two events are independent if the probability that one event occurs on any given trial of an experiment is not affected or changed by the occurrence of the other event. When are trials not independent? Imagine that these coins were spread out so that half were heads up and half ...
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... Definition: A random variable X is a numerical valued function defined on a sample space. It assigns one numerical value to each point in the sample space. A discrete random variable is a random variable whose possible values form a finite or countable infinite set of numbers. Example: Number of hea ...
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Stats SB Notes 4.1 Completed.notebook
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... • Find the probability of each possible outcome by dividing  its frequency by the sum of the frequencies. • Check that each probability is between 0 and 1 and that the  sum is 1. ...
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... .06 and the intersection of these tow values is the area. Result is 0.3962. Example 6.3 Area between 0 and Negative z Since Z (-1.26 for this example) is negative, we know that it is to the left of the mean. Remember that the mean in the standard normal curve is zero. In the last example, we found t ...
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Probability

Probability is the measure of the likeliness that an event will occur. Probability is quantified as a number between 0 and 1 (where 0 indicates impossibility and 1 indicates certainty). The higher the probability of an event, the more certain we are that the event will occur. A simple example is the toss of a fair (unbiased) coin. Since the two outcomes are equally probable, the probability of ""heads"" equals the probability of ""tails"", so the probability is 1/2 (or 50%) chance of either ""heads"" or ""tails"".These concepts have been given an axiomatic mathematical formalization in probability theory (see probability axioms), which is used widely in such areas of study as mathematics, statistics, finance, gambling, science (in particular physics), artificial intelligence/machine learning, computer science, game theory, and philosophy to, for example, draw inferences about the expected frequency of events. Probability theory is also used to describe the underlying mechanics and regularities of complex systems.
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