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Week5
Week5

... that the corporations intranet has been suffering with a number of faults and is unavailable much of the time. He arranges for the collection of data which details the number of times where the intranet has been down, and for how long, over the last three hundred business days. The results are given ...
投影片 1
投影片 1

... • Give an example of a single point in the sample space? • How might you depict the full sample space? • What is an example of an “event”? ...
Compound Event Probability
Compound Event Probability

Statistics and Probability
Statistics and Probability

... Probability distribution of a discrete variable becomes more normal as sample size increases. Learning Competencies Students will be able to  define a random variable, assign probabilities to its sample space, and graph the distribution of the random variable.  calculate and interpret in context t ...
Game of Chuck-a-Luck - UH - Department of Mathematics
Game of Chuck-a-Luck - UH - Department of Mathematics

Formalizing Probability Choosing the Sample Space Probability
Formalizing Probability Choosing the Sample Space Probability

Objective : The student will be able to determine sample spaces
Objective : The student will be able to determine sample spaces

Theoretical vs Experimental Probability
Theoretical vs Experimental Probability

ITS336 Lecture 10. Tree Diagrams and Bayes` Theorem
ITS336 Lecture 10. Tree Diagrams and Bayes` Theorem

A "hand" of 5 cards is dealt from a thoroughly shuffled deck of cards
A "hand" of 5 cards is dealt from a thoroughly shuffled deck of cards

Chapter 4
Chapter 4

Statistical Analysis of Gene Expression Data (A Large Number of
Statistical Analysis of Gene Expression Data (A Large Number of

Lecture 5.1
Lecture 5.1

... Recall from section 2.5: Two events A and B are independent when P ( A ∩ B ) = P ( A) ∗ P (B ) . If we remember that p(x, y) = P(X = x, Y = y) should be interpreted as p ( x, y ) = P ( X = x and Y = y ) = P ( X = x ∩ Y = y ) then it makes sense to state the following definition: Two discrete random ...
A Guide to Using Probability
A Guide to Using Probability

Name - Garnet Valley School
Name - Garnet Valley School

... e. In how many different ways could they select a pitcher, a catcher, and a first baseman? You Try 1. A card is drawn at random from a normal 52-card deck. a. What name is given to the act of drawing the card? ...
Probability:
Probability:

... a definite outcome. Usually the outcome is in the form of a description, count, or measurement. For example: If you toss a coin, there are only 2 possible outcomes (heads or tails). Sample Space - set of all possible outcomes. It is especially convenient to know the sample space where all outcomes a ...
Interactive Note Book (INB) Please copy all the notes in INB and I
Interactive Note Book (INB) Please copy all the notes in INB and I

Midterm-2 - Math @ McMaster University
Midterm-2 - Math @ McMaster University

Binomial Distribution
Binomial Distribution

Slide 1
Slide 1

... • Suppose we have an unfair coin and wish to estimate the outcome (head or tail) from observing a series of coin tosses. • q = probability of tossing a head. ...
Naïve Bayes Classifier The Naïve Bayes Classifier is
Naïve Bayes Classifier The Naïve Bayes Classifier is

PPT - School of Computer Science
PPT - School of Computer Science

... In any one game, each is equally likely to win What is most likely length of a “best of 7” series? Flip coins until either 4 heads or 4 tails Is this more likely to take 6 or 7 flips? ...
Hypothesis testing
Hypothesis testing

1. The discrete random variable X has a PMF described by the table
1. The discrete random variable X has a PMF described by the table

Equally Likely outcomes
Equally Likely outcomes

... Coincidence: The Birthday Problem The event E c corresponds to the set of lists where all birthdays on the list are different.. By the multiplication principle there are 365 · 364 · 363 · 362 · · · 345 = P(365, 20) such lists (a 51-digit number). Now P(E c ) = P(365, 20)/36520 ≈ 0.588 and hence P(E ...
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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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