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Introduction to Probability
Charles Grinstead; J. Laurie Snell · American Mathematical Society · 2006
Probability theory began in seventeenth century France when the two great French mathematicians, Blaise Pascal and Pierre de Fermat, corresponded over two problems from games of chance. Problems like those Pascal and Fermat solved continuedto influence such early researchers as Huygens, Bernoulli, and DeMoivre in establishing a mathematical theory of probability. Today, probability theory is a wellestablished branch of mathematics that finds applications in every area of scholarlyactivity from music to physics, and in daily experience from weather prediction topredicting the risks of new medical treatments. This text is designed for an introductory probability course taken by sophomores,juniors, and seniors in mathematics, the physical and social sciences, engineering,and computer science. It presents a thorough treatment of probability ideas andtechniques necessary for a form understanding of the subject. The text can be usedin a variety of course lengths, levels, and areas of emphasis. For use in a standard one-term course, in which both discrete and continuousprobability is covered, students should have taken as a prerequisite two terms ofcalculus, including an introduction to multiple integrals. In order to cover Chapter 11, which contains material on Markov chains, some knowledge of matrix theoryis necessary. The text can also be used in a discrete probability course. The material has beenorganized in such a way that the discrete and continuous probability discussions arepresented in a separate, but parallel, manner. This organization dispels an overlyrigorous or formal view of probability and o?ers some strong pedagogical valuein that the discrete discussions can sometimes serve to motivate the more abstractcontinuous probability discussions. For use in a discrete probability course, studentsshould have taken one term of calculus as a prerequisite. Very little computing background is assumed or necessary in order to obtain fullbenefits from the use of the comp
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MAT 117: Mathematical Problem Solving in Liberal Arts
LibreTexts
In the contents: 01: Voting Theory · 5.01: Prelude to Sequences Probability and Counting Theory · 10: Graph Theory
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Free Energy 1e (Snee)
Preston Snee · University of Illinois Chicago
In the contents: 10: The Kinetic Theory of Gas · 10.01: Probability vs. Probability Distribution · 12.01: Einsteins Theory of Relativity
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Math In Plain Sight
Timothy Cooley · Orange Coast College
In the contents: 2.01: Set Theory · 05: Probability · 5.01: Probability Basics
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Physical Science for Educators Volume 1
Timothy Evans, Kylee Ford, Kenneth Henry, Yogita Kumari, Claude Mona & Suzanne Wakim · Coalinga College
In the contents: 2.2.21: Probability · 03: Atomic Theory and Periodic Table · 3.2.01: Basic Atomic Theory
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Behavioral Statistics
Michelle Oja · Taft College
In the contents: 5.02: Introduction to Probability
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Thermodynamics and Statistical Mechanics
Daniel Arovas · UC San Diego
In the contents: 01: Fundamentals of Probability · 1.02: Basic Concepts in Probability Theory · 1.03: Entropy and Probability
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Probability, Mathematical Statistics, and Stochastic Processes
Kyle Siegrist · University of Alabama in huntsville
In the contents: 02: Probability Spaces · 2.03: Probability Measures · 2.04: Conditional Probability
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System Design for Uncertainty
Franz S. Hover & Michael S. Triantafyllou · Massachusetts Institute of Technology
In the contents: 03: Probability · 3.02: Conditional Probability · 3.05: Continuous Random Variables and the Probability Density Function
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Introductory Statistics
Barbara Illowsky & Susan Dean · De Anza College
In the contents: 1.01: Definitions of Statistics Probability and Key Terms · 03: Probability Topics · 3.03: Two Basic Rules of Probability
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Living With Earthquakes in The Pacific Northwest
Robert S. Yeats · Oregon State University
In the contents: 5.7.04: The Seismic Gap Theory · 5.7.12: The 1990 Probability Forecast
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Precalculus
Jay Abramson · OpenStax
In the contents: 11: Sequences Probability and Counting Theory · 11.01: Introduction to Sequences Probability and Counting Theory · 11.08: Probability
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Data Analysis Certificate Program
Alex Mata · Calbright College
In the contents: 13: Probability Sampling and Estimation · 13.01: Prelude to Probability Sampling and Estimation · 13.02: How are Probability and Statistics Different
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Math C100: Liberal Arts Mathematics
Chau D. Tran · Coastline College
In the contents: 04: Probability and Odds · 4.02: Conditional Probability · 8.03: Voting Theory
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MAT 1350: Precalculus Part I
Jay Abramson · Prince George's Community College
In the contents: 13: Sequences Probability and Counting Theory · 13.00: Prelude to Sequences Probability and Counting Theory · 13.07: Probability
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General Biology
OpenStax · LibreTexts
In the contents: 3.2.02: Mendels Experiments and the Laws of Probability · 3.3.02: Chromosomal Theory and Genetic Linkage
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Draft Custom Version MAT 131 College Algebra
LibreTexts
In the contents: 09: Sequences Probability and Counting Theory
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CHEM 210: General Chemistry I, An "Atoms Up" Approach
Camille Kaslan · Canada College
In the contents: 4.2.01: Dalton's Atomic Theory · 5.7.01: Visualizing Atomic Orbitals as Probability Densities · 9.01: Valence Bond Theory - Bonds as Orbital Overlaps
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Research and Design for Emergency Services
Peter Loebach · Arapahoe Community College
In the contents: 2.05: Linking Methods with Theory- Micro meso and macro approaches · 6.02: Probability Sampling · 6.03: Non-Probability Sampling
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Math for Educators (MATH 010A and 010B CID120)
Lynn Mann · LibreTexts
In the contents: 1.4.15: High School Statistics and Probability Standards · 04: Number Theory · 4.01: Introduction to Number Theory