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MTH 202 : Probability and Statistics
MTH 202 : Probability and Statistics

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Chapter 6 Probability

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... 11.   even  number  or  a  number  greater  than  8   12.   odd  number  or  a  number  less  than  5   13.   multiple  of  2  or  a  multiple  of  3   14.   a  multiple  of  5  or  a  multiple  of  6   15.   a  multiple ...
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...  Prob(E) = |E|/ |S|  In the above example, p(E) = 2/4 = 0.5 Question: what is the probability of getting at least one six in three roles of a die? ...
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... 1. Suppose our experiment is we flip a coin and record whether it lands heads or tails. Then we write our sample space as S = { heads, tails } or we may write S = {h,t}. This is a discrete sample space since it consists of discrete data. 2. Suppose our experiment is to flip a coin 4 times and record ...
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... x assumes a value between two given numbers a and b. 2. x < a, the event that the random variable x assumes a value less than a given number a 3. b < x, the event that the random variable x assumes a value greater than a given number b (this can also be x > b) ...
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... a. In how many different ways can a student check off one answer to each probability? b. In how many different ways can a student check off one answer to each question and get all the ...
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... row n = 0 at the top. The entries in each row are numbered from the left beginning with k = 0 and are usually staggered relative to the numbers in the adjacent rows. A simple construction of the triangle proceeds in the following manner. On row 0, write only the number 1. Then, to construct the elem ...
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MATH 2620 B

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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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