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chapter2 part I
chapter2 part I

Lecture 5
Lecture 5

Document
Document

Discrete probability distributions
Discrete probability distributions

... distributions by combining methods of descriptive statistics from Chapters 2 and 3 and those of probability presented in Chapter 4.  A probability distribution, in general, will describe what will probably happen instead of what actually did happen ...
Example Toss a coin. Sample space: S = {H, T} Example: Rolling a
Example Toss a coin. Sample space: S = {H, T} Example: Rolling a

Unit 13: Systems of equations
Unit 13: Systems of equations

Section 4.3 Homework Answers
Section 4.3 Homework Answers

... I want to calculate P(Y < 1.5), but I recognize that it would be simpler if we calculated instead P(Y > 1.5) the complement of what I really want. Thus P(Y < 1.5) = 1 – P(Y > 1.5) ...
Chapter 4 - Practice Problems 1
Chapter 4 - Practice Problems 1

... 1) In the relative frequency formula, the probabilities are determined by conducting an experiment, counting the number of occurrences of the event, and creating the ratio of number of occurrences to number of times the experiment was conducted. In the classical approach, a sample space of all of th ...
Chapter 2 solutions
Chapter 2 solutions

3. Probability Theory
3. Probability Theory

6.1 The Idea of Probability
6.1 The Idea of Probability

... • A phenomenon in which individual outcomes are uncertain, but there is nonetheless a regular distribution of outcomes in a large # of repetitions. – Random not synonym for ‘haphazard’, but description of order which emerges only in a long run of events. ...
6.1 - 6.2 Applications
6.1 - 6.2 Applications

... example, if a game results in one H and thee T, Brian loses $2]. Brian’s possible outcomes are {-4, -2, 0, 2, 4}. Assign probabilities to these outcomes by playing the game 20 times [or simulating 20 times] and using the proportions of the outcomes to estimate the probabilities. Combine your trials ...
The Drunkard`s Walk: How Randomness Rules Our Lives
The Drunkard`s Walk: How Randomness Rules Our Lives

... importance to memories that are most vivid (and hence most available for retrieval) i. Which is greater? 1. # of 6-letter English words having an n as the fifth letter 2. # of 6-letter English words ending in ing ? c. “A good story is often less probable than a less satisfactory [explanation]” (Kahn ...
Probablity Models have 3 components: Sample Space (Ω) Events on
Probablity Models have 3 components: Sample Space (Ω) Events on

Introduction to the Practice of Statistics
Introduction to the Practice of Statistics

event - Gordon State College
event - Gordon State College

... INFERENTIAL STATISTICS If, under a given assumption (such as a lottery being fair), the probability of a particular observed event (such as five consecutive lottery wins) is extremely small, we conclude that the assumption is probably not correct. Statisticians use the rare event rule for inferentia ...
Document
Document

Unit 1 Probability of One Event Introduction
Unit 1 Probability of One Event Introduction

Probability
Probability

Powerpoint
Powerpoint

Introduction to probability Coin flipping problems, etc.
Introduction to probability Coin flipping problems, etc.

... What is the probability that a five-card poker hand contains two pairs (that is, two of each of two different kinds and a fifth card of a third kind)? In total, there are C(52, 5) ways to draw a hand (this is our |S|). We want to choose 2 out of four cards of one value, 2 out of four cards of anothe ...
Chapter 4 ntoes - Clinton Public Schools
Chapter 4 ntoes - Clinton Public Schools

... _______________________ is any collection of results or outcomes of an experiment. _______________________ is an outcome or an event that cannot be broken down any further. _______________________for an experiment consists of all possible simple events. Experiment Event Single Event Sample Spaces ...
10.4 - Independent and Dependent v2
10.4 - Independent and Dependent v2

Chapter 14: Probability
Chapter 14: Probability

... obtained were likely to occur simply by chance. To determine if our results are statistically significant, we need calculate the probability, which is what we will study in the next chapter. ...
7.3 - Independent and Dependent v2
7.3 - Independent and Dependent v2

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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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