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Introduction to College Mathematics
Unrestricted Use
CC BY
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This textbook is an introduction to college mathematics. It covers set theory, logic, numeration systems, probability, modular arithmetic, and measurement.

Subject:
Mathematics
Material Type:
Textbook
Provider:
Achieving the Dream
Author:
Hostos Community College
Tanvir Price
Date Added:
05/20/2021
Introduction to Statistics
Unrestricted Use
Public Domain
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Introduction to Statistics is a resource for learning and teaching introductory statistics. This work is in the public domain. Therefore, it can be copied and reproduced without limitation. However, we would appreciate a citation where possible. Please cite as: Online Statistics Education: A Multimedia Course of Study (http://onlinestatbook.com/). Project Leader: David M. Lane, Rice University. Instructor's manual, PowerPoint Slides, and additional questions are available.

Subject:
Mathematics
Statistics and Probability
Material Type:
Textbook
Author:
David Lane
Date Added:
08/13/2020
Introduction to Statistics
Unrestricted Use
CC BY
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This course covers descriptive statistics, the foundation of statistics, probability and random distributions, and the relationships between various characteristics of data. Upon successful completion of the course, the student will be able to: Define the meaning of descriptive statistics and statistical inference; Distinguish between a population and a sample; Explain the purpose of measures of location, variability, and skewness; Calculate probabilities; Explain the difference between how probabilities are computed for discrete and continuous random variables; Recognize and understand discrete probability distribution functions, in general; Identify confidence intervals for means and proportions; Explain how the central limit theorem applies in inference; Calculate and interpret confidence intervals for one population average and one population proportion; Differentiate between Type I and Type II errors; Conduct and interpret hypothesis tests; Compute regression equations for data; Use regression equations to make predictions; Conduct and interpret ANOVA (Analysis of Variance). (Mathematics 121; See also: Biology 104, Computer Science 106, Economics 104, Psychology 201)

Subject:
Mathematics
Statistics and Probability
Material Type:
Full Course
Provider:
The Saylor Foundation
Date Added:
06/03/2021
Introduction to Statistics (MATH 146)
Unrestricted Use
CC BY
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The main goal of the course is to highlight the general assumptions and methods that underlie all statistical analysis. The purpose is to get a good understanding of the scope, and the limitations of these methods. We also want to learn as much as possible about the assumptions behind the most common methods, in order to evaluate if they apply with reasonable accuracy to a given situation. Our goal is not so much learning bread and butter techniques: these are pre-programmed in widely available and used software, so much so that a mechanical acquisition of these techniques could be quickly done "on the job". What is more challenging is the evaluation of what the results of a statistical procedure really mean, how reliable they are in given circumstances, and what their limitations are.Login: guest_oclPassword: ocl

Subject:
Mathematics
Statistics and Probability
Material Type:
Full Course
Homework/Assignment
Lecture Notes
Lesson Plan
Syllabus
Provider:
Washington State Board for Community & Technical Colleges
Provider Set:
Open Course Library
Date Added:
10/31/2011
Introductory Business Statistics
Unrestricted Use
CC BY
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The book "Introductory Business Statistics" by Thomas K. Tiemann explores the basic ideas behind statistics, such as populations, samples, the difference between data and information, and most importantly sampling distributions. The author covers topics including descriptive statistics and frequency distributions, normal and t-distributions, hypothesis testing, t-tests, f-tests, analysis of variance, non-parametric tests, and regression basics. Using real-world examples throughout the text, the author hopes to help students understand how statistics works, not just how to "get the right number."

Subject:
Mathematics
Statistics and Probability
Material Type:
Textbook
Provider:
BCcampus
Provider Set:
BCcampus Open Textbooks
Author:
Thomas K. Tiemann
Date Added:
08/13/2020
Introductory Business Statistics
Unrestricted Use
CC BY
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Introductory Business Statistics is designed to meet the scope and sequence requirements of the one-semester statistics course for business, economics, and related majors. Core statistical concepts and skills have been augmented with practical business examples, scenarios, and exercises. The result is a meaningful understanding of the discipline, which will serve students in their business careers and real-world experiences.

Subject:
Mathematics
Statistics and Probability
Material Type:
Textbook
Provider:
Rice University
Provider Set:
OpenStax College
Author:
Alexander Holmes
Barbara Illowsky
Susan Dean
Veda Roodal Persad
Date Added:
11/30/2017
Lies, Damned Lies, or Statistics: How to Tell the Truth with Statistics
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CC BY-SA
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This is a first draft of a free (as in speech, not as in beer, [Sta02]) (although it is free as in beer as well) textbook for a one-semester, undergraduate statistics course. It was used for Math 156 at Colorado State University–Pueblo in the spring semester of 2017.

Subject:
Mathematics
Statistics and Probability
Material Type:
Textbook
Author:
Jonathan A. Poritz
Date Added:
08/13/2020
Math Explained
Conditional Remix & Share Permitted
CC BY-NC-SA
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Mathematics explained: Here you find videos on various math topics:

Pre-university Calculus (functions, equations, differentiation and integration)
Vector calculus (preparation for mechanics and dynamics courses)
Differential equations, Calculus
Functions of several variables, Calculus
Linear Algebra
Probability and Statistics

Subject:
Mathematics
Material Type:
Lecture
Provider:
Delft University of Technology
Provider Set:
Delft University OpenCourseWare
Date Added:
08/13/2020
Models, Data and Inference for Socio-Technical Systems, Spring 2007
Conditional Remix & Share Permitted
CC BY-NC-SA
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In this class, students use data and systems knowledge to build models of complex socio-technical systems for improved system design and decision-making. Students will enhance their model-building skills, through review and extension of functions of random variables, Poisson processes, and Markov processes; move from applied probability to statistics via Chi-squared t and f tests, derived as functions of random variables; and review classical statistics, hypothesis tests, regression, correlation and causation, simple data mining techniques, and Bayesian vs. classical statistics. A class project is required.

Subject:
Mathematics
Statistics and Probability
Material Type:
Full Course
Provider:
MIT
Provider Set:
MIT OpenCourseWare
Author:
Frey, Daniel
Date Added:
01/01/2007
Mostly Harmless Statistics
Conditional Remix & Share Permitted
CC BY-SA
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0.0 stars

This text is for an introductory level probability and statistics course with an intermediate algebra prerequisite. The focus of the text follows the American Statistical Association’s Guidelines for Assessment and Instruction in Statistics Education (GAISE). Software examples provided for Microsoft Excel, TI-84 & TI-89 calculators. A separate document is provided on the website with examples in
SPSS.

Students new to statistics are sure to benefit from this fully ADA accessible and relevant textbook. The examples resonate with everyday life, the text is approachable, and has a conversational tone to provide an inclusive and easy to read format for students.

This textbook incorporates the compilation of my notes over the years teaching introductory probability and statistics courses used to expand and enhance upon the open educational resource Statistics Using Technology by Kathryn Kozak, with some additional material adapted from OpenIntro Statistics by Diez,
Barr, and Çetinkaya-Rundel. Both texts are licensed under CC BY-SA 4.0. This textbook, except for the cover art, is licensed under a Creative Commons Attribution-Share Alike 4.0 International License (CCBY-SA 4.0).

Review and content editing by Jennifer Ward. Recommended definition edits and glossary terms by Dr. Naghmeh Daneshi. Alternative text for images provided by Whitney Cave. Additional exercises from Whitney Cave and from MyOpenMath: https://www.myopenmath.com/. Copy editing by Walter Benson. Cover art by James Tadlock https://www.artstation.com/redhedron.

For instructors, there is a complete solution manual and two companion online homework courses. An adaptive learning system called Realizeit which has content from the text, videos and homework problems. A free MyOpenMath course with problems divided by chapter. Email Rachel Webb for more information.

Subject:
Mathematics
Statistics and Probability
Material Type:
Textbook
Date Added:
09/21/2023
Perfect secrecy
Conditional Remix & Share Permitted
CC BY-NC-SA
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Claude Shannon's idea of perfect secrecy: no amount of computational power can help improve your ability to break the one-time pad. Created by Brit Cruise.

Subject:
Computer Science
Information Technology
Life Science
Physical Science
Material Type:
Lesson
Provider:
Khan Academy
Provider Set:
Code.org
Author:
Brit Cruise
Date Added:
08/10/2021
Plinko Probability
Unrestricted Use
CC BY
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0.0 stars

The students will play a classic game from a popular show. Through this they will see the probabilty that the ball will land each of the numbers with more accurate results coming from repeated testing.

Subject:
Mathematics
Statistics and Probability
Material Type:
Simulation
Provider:
University of Colorado Boulder
Provider Set:
PhET Interactive Simulations
Author:
Michael Dubson
Date Added:
11/16/2007
Presentation: 3.1 Introduction to Probability
Unrestricted Use
CC BY
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In this section, you will be introduced to the concept of probability and how it applies to real-world problems. You will learn important vocabulary in probability theory including simple event, event, sample space. You will learn the difference between mutually exclusive and independent events.

Subject:
Mathematics
Statistics and Probability
Material Type:
Lecture Notes
Lesson
Author:
Kim Massaro
Date Added:
05/11/2022
Presentation: 3.2 Types of Probabilities
Unrestricted Use
CC BY
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In the previous section, you were introduced to the basic concepts of probability theory. In this section you’ll learn how to apply the theory to calculating various types of probabilities using two-way tables (contingency tables).

Subject:
Mathematics
Statistics and Probability
Material Type:
Lecture Notes
Lesson
Author:
Kim Massaro
Date Added:
05/11/2022
Probabilistic Systems Analysis and Applied Probability, Fall 2010
Conditional Remix & Share Permitted
CC BY-NC-SA
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Welcome to 6.041/6.431, a subject on the modeling and analysis of random phenomena and processes, including the basics of statistical inference. Nowadays, there is broad consensus that the ability to think probabilistically is a fundamental component of scientific literacy. For example: The concept of statistical significance (to be touched upon at the end of this course) is considered by the Financial Times as one of "The Ten Things Everyone Should Know About Science". A recent Scientific American article argues that statistical literacy is crucial in making health-related decisions. Finally, an article in the New York Times identifies statistical data analysis as an upcoming profession, valuable everywhere, from Google and Netflix to the Office of Management and Budget. The aim of this class is to introduce the relevant models, skills, and tools, by combining mathematics with conceptual understanding and intuition.

Subject:
Computer Science
Information Science
Information Technology
Mathematics
Statistics and Probability
Material Type:
Full Course
Provider:
MIT
Provider Set:
MIT OpenCourseWare
Author:
Bertsekas, Dimitri
Tsitsiklis, John
Date Added:
01/01/2010
Probability And Its Applications To Reliability, Quality Control, And Risk Assessment, Fall 2005
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CC BY-NC-SA
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Interpretations of the concept of probability. Basic probability rules; random variables and distribution functions; functions of random variables. Applications to quality control and the reliability assessment of mechanical/electrical components, as well as simple structures and redundant systems. Elements of statistics. Bayesian methods in engineering. Methods for reliability and risk assessment of complex systems, (event-tree and fault-tree analysis, common-cause failures, human reliability models). Uncertainty propagation in complex systems (Monte Carlo methods, Latin Hypercube Sampling). Introduction to Markov models. Examples and applications from nuclear and chemical-process plants, waste repositories, and mechanical systems. Open to qualified undergraduates.

Subject:
Mathematics
Statistics and Probability
Material Type:
Full Course
Provider:
MIT
Provider Set:
MIT OpenCourseWare
Author:
Golay, Michael
Date Added:
01/01/2005
Probability: Birthday Probability Problem
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CC BY-NC-SA
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This lesson is a birthday problem that determines the probability that at least 2 people in a room of 30 share the same birthday. [Probability playlist: Lesson 17 of 29]

Subject:
Mathematics
Statistics and Probability
Material Type:
Lecture
Provider:
Khan Academy
Provider Set:
Khan Academy
Author:
Salman Khan
Date Added:
08/13/2020