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This textbook is part of the OpenIntro Statistics series and offers complete coverage of the high school AP Statistics curriculum. Real data and plenty of inline examples and exercises make this an engaging and readable book. Links to lecture slides, video overviews, calculator tutorials, and video solutions to selected end of chapter exercises make this an ideal choice for any high school or Community College teacher. In fact, Portland Community College recently adopted this textbook for its Introductory Statistics course, and it estimates that this will save their students \$250,000 per year. Find out more at: openintro.org/ahss

View our video tutorials here:
openintro.org/casio
openintro.org/TI

Subject:
Mathematics
Statistics and Probability
Material Type:
Textbook
Provider:
OpenIntro
Author:
Christopher Barr
David Diez
Leah Dorazio
Mine Cetinkaya-Rundel
08/13/2020
Unrestricted Use
CC BY
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Applied Finite Mathematics covers topics including linear equations, matrices, linear programming, the mathematics of finance, sets and counting, probability, Markov chains, and game theory. Endorsed by CollegeOpenTextbooks.org.

Subject:
Finance
Material Type:
Full Course
Textbook
Provider:
Rice University
Provider Set:
Connexions
Author:
Rupinder Sekhon
08/13/2020
Unrestricted Use
CC BY
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This is a "first course" in the sense that it presumes no previous course in probability. The units are modules taken from the unpublished text: Paul E. Pfeiffer, ELEMENTS OF APPLIED PROBABILITY, USING MATLAB. The units are numbered as they appear in the text, although of course they may be used in any desired order. For those who wish to use the order of the text, an outline is provided, with indication of which modules contain the material.

Subject:
Mathematics
Statistics and Probability
Material Type:
Full Course
Provider:
Rice University
Provider Set:
OpenStax CNX
Author:
Paul E. Pfeiffer
09/18/2009
Unrestricted Use
CC BY
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0.0 stars

Biology is designed for multi-semester biology courses for science majors. It is grounded on an evolutionary basis and includes exciting features that highlight careers in the biological sciences and everyday applications of the concepts at hand. To meet the needs of today&rsquo;s instructors and students, some content has been strategically condensed while maintaining the overall scope and coverage of traditional texts for this course. Instructors can customize the book, adapting it to the approach that works best in their classroom. Biology also includes an innovative art program that incorporates critical thinking and clicker questions to help students understand&mdash;and apply&mdash;key concepts.

Subject:
Biology
Life Science
Material Type:
Full Course
Provider:
Rice University
Provider Set:
OpenStax College
08/12/2021
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CC BY-NC
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Subject:
Biology
Life Science
Material Type:
Module
Author:
OER Librarian
08/12/2021
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CC BY-NC
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By the end of this section, you will be able to:Describe the scientific reasons for the success of Mendel’s experimental workDescribe the expected outcomes of monohybrid crosses involving dominant and recessive allelesApply the sum and product rules to calculate probabilities

Subject:
Biology
Life Science
Material Type:
Module
Author:
OER Librarian
08/12/2021
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CC BY-NC-SA
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Introduces students to the basic tools in using data to make informed management decisions. Covers introductory probability, decision analysis, basic statistics, regression, simulation, and linear and nonlinear optimization. Computer spreadsheet exercises and examples drawn from marketing, finance, operations management, and other management functions. Restricted to Sloan Fellows.

Subject:
Finance
Marketing
Mathematics
Statistics and Probability
Material Type:
Full Course
Provider:
MIT
Provider Set:
MIT OpenCourseWare
Author:
Carroll, John S.
01/01/2003
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CC BY-NC-SA
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Covers computational and data analysis techniques for environmental engineering applications. First third of subject introduces MATLAB and numerical modeling. Second third emphasizes probabilistic concepts used in data analysis. Final third provides experience with statistical methods for analyzing field and laboratory data. Numerical techniques such as Monte Carlo simulation are used to illustrate the effects of variability and sampling. Concepts are illustrated with environmental examples and data sets. This subject is a computer-oriented introduction to probability and data analysis. It is designed to give students the knowledge and practical experience they need to interpret lab and field data. Basic probability concepts are introduced at the outset because they provide a systematic way to describe uncertainty. They form the basis for the analysis of quantitative data in science and engineering. The MATLABĺ¨ programming language is used to perform virtual experiments and to analyze real-world data sets, many downloaded from the web. Programming applications include display and assessment of data sets, investigation of hypotheses, and identification of possible casual relationships between variables. This is the first semester that two courses, Computing and Data Analysis for Environmental Applications (1.017) and Uncertainty in Engineering (1.010), are being jointly offered and taught as a single course.

Subject:
Education
Engineering
Environmental Engineering
Mathematics
Material Type:
Full Course
Provider:
MIT
Provider Set:
MIT OpenCourseWare
Author:
McLaughlin, Dennis
McLaughlin, Dennis B.
01/01/2003
Unrestricted Use
CC BY
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Simulate the original experiment that proved that electrons can behave as waves. Watch electrons diffract off a crystal of atoms, interfering with themselves to create peaks and troughs of probability.

Subject:
Physical Science
Physics
Material Type:
Simulation
Provider:
Provider Set:
PhET Interactive Simulations
Author:
Carl Wieman
Kathy Perkins
Sam McKagan
Sam Reid
10/02/2006
Conditional Remix & Share Permitted
CC BY-NC-SA
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0.0 stars

Discrete stochastic processes are essentially probabilistic systems that evolve in time via random changes occurring at discrete fixed or random intervals. This course aims to help students acquire both the mathematical principles and the intuition necessary to create, analyze, and understand insightful models for a broad range of these processes. The range of areas for which discrete stochastic-process models are useful is constantly expanding, and includes many applications in engineering, physics, biology, operations research and finance.

Subject:
Finance
Material Type:
Full Course
Provider:
MIT
Provider Set:
MIT OpenCourseWare
Author:
Gallager, Robert
01/01/2011
Unrestricted Use
CC BY
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Explore tunneling splitting in double well potentials. This classic problem describes many physical systems, including covalent bonds, Josephson junctions, and two-state systems such as spin 1/2 particles and ammonia molecules.

Subject:
Physical Science
Physics
Material Type:
Simulation
Provider:
Provider Set:
PhET Interactive Simulations
Author:
Carl Wieman
Chris Malley
Kathy Perkins
Sam McKagan
10/04/2006
Conditional Remix & Share Permitted
CC BY-NC-SA
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This course emphasizes three methodologies - reliability and probabilistic risk assessment (RPRA), decision analysis (DA), and cost-benefit analysis (CBA). In this class, the issues of interest are: the risks associated with large engineering projects such as nuclear power reactors, the International Space Station, and critical infrastructures; the development of new products; the design of processes and operations with environmental externalities; and infrastructure renewal projects.

Subject:
Engineering
Environmental Engineering
Material Type:
Full Course
Provider:
MIT
Provider Set:
MIT OpenCourseWare
Author:
Apostolakis, George
01/01/2007
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CC BY-NC-SA
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Continues 18.100. Roughly half the subject devoted to the theory of the Lebesgue integral with applications to probability, and half to Fourier series and Fourier integrals.

Subject:
Mathematics
Material Type:
Full Course
Provider:
MIT
Provider Set:
MIT OpenCourseWare
Author:
Melrose, Richard B.
01/01/2004
Unrestricted Use
CC BY
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Learn how to make waves of all different shapes by adding up sines or cosines. Make waves in space and time and measure their wavelengths and periods. See how changing the amplitudes of different harmonics changes the waves. Compare different mathematical expressions for your waves.

Subject:
Physical Science
Physics
Material Type:
Simulation
Provider:
Provider Set:
PhET Interactive Simulations
Author:
Carl Wieman
Chris Malley
Danielle Harlow
Sam McKagan
10/02/2006
Conditional Remix & Share Permitted
CC BY-NC-SA
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0.0 stars

Can you tell the difference between actions based upon flipping a coin and those based upon blind guessing or simulating randomness? This short video examines the frequency stability property. Created by Brit Cruise.

Subject:
Computer Science
Information Technology
Life Science
Physical Science
Material Type:
Lesson
Provider:
Provider Set:
Code.org
Author:
Brit Cruise
08/10/2021
Unrestricted Use
CC BY
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This resource contains class notes and exercises for a course on Fundamental Statistics. Each section is provided in its own Google Doc to allow for remixing and adapting as needed.

Subject:
Mathematics
Statistics and Probability
Material Type:
Textbook
09/21/2023
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CC BY-NC-SA
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" An historical examination and analysis of the evolution and development of games and game mechanics. Topics include a large breadth of genres and types of games, including sports, game shows, games of chance, schoolyard games, board games, roleplaying games, and digital games. Students submit essays documenting research and analysis of a variety of traditional and eclectic games. Project teams required to design, develop, and thoroughly test their original games."

Subject:
Anthropology
Social and Behavioral Sciences
Material Type:
Full Course
Provider:
MIT
Provider Set:
MIT OpenCourseWare
Author:
Fernandez-Vara, Clara
Juul, Jesper
Rusch, Doris
Tan, Philip
01/01/2008
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CC BY-NC-SA
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Unified theory of information with applications to computing, communications, thermodynamics, and other sciences. Digital signals and streams, codes, compression, noise, and probability. Reversible and irreversible operations. Information in biological systems. Channel capacity. Maximum-entropy formalism. Thermodynamic equilibrium, temperature. The Second Law of Thermodynamics. Quantum computation.

Subject:
Biology
Life Science
Material Type:
Full Course
Provider:
MIT
Provider Set:
MIT OpenCourseWare
Author:
Lloyd, Seth