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  • Statistics and Probability
Introduction to Applied Statistics, Summer 2011
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This course provides graduate students in the sciences with an intensive introduction to applied statistics. Topics include descriptive statistics, probability, non-parametric methods, estimation methods, hypothesis testing, correlation and linear regression, simulation, and robustness considerations. Calculations will be done using handheld calculators and the Minitab Statistical Computer Software.

Subject:
Mathematics
Statistics and Probability
Material Type:
Full Course
Reading
Syllabus
Provider:
UMass Boston
Provider Set:
UMass Boston OpenCourseWare
Author:
Eugene Gallagher
Date Added:
05/23/2019
Introduction to Statistical Methods in Economics, Spring 2009
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" This course will provide a solid foundation in probability and statistics for economists and other social scientists. We will emphasize topics needed for further study of econometrics and provide basic preparation for 14.32. Topics include elements of probability theory, sampling theory, statistical estimation, and hypothesis testing."

Subject:
Business and Finance
Economics
Mathematics
Social Science
Statistics and Probability
Material Type:
Full Course
Provider:
M.I.T.
Provider Set:
M.I.T. OpenCourseWare
Author:
Menzel, Konrad
Date Added:
01/01/2009
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:
10/24/2019
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
Introduction to Statistics for Psychology
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CC BY
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Includes an attached common course cartdridge for an Introduction to Statistics for Psychology course adapted by Paul C. Bernhardt, Ph.D. for a PSYC 301 course at Frostburg State University. The course is an adaptation of Learning Statistics with jamovi, A Tutorial for Psychology Students and Other Beginners (Navarro & Foxcraft, 2019) and a free and open-source statistical analysis package named jamovi (www.jamovi.org).

Subject:
Psychology
Social Science
Statistics and Probability
Material Type:
Activity/Lab
Assessment
Full Course
Homework/Assignment
Author:
Paul Bernhardt
Date Added:
06/02/2021
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
Introductory Business Statistics with Interactive Spreadsheets - 1st Canadian Edition
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CC BY
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"Introductory Business Statistics with Interactive Spreadsheets - 1st Canadian Edition" is an adaptation of Thomas K. Tiemann's book, "Introductory Business Statistics". In addition to covering basics such as populations, samples, the difference between data and information, and sampling distributions, descriptive statistics and frequency distributions, normal and t-distributions, hypothesis testing, t-tests, f-tests, analysis of variance, non-parametric tests, and regression basics, the following information has been added: the chi-square test and categorical variables, null and alternative hypotheses for the test of independence, simple linear regression model, least squares method, coefficient of determination, confidence interval for the average of the dependent variable, and prediction interval for a specific value of the dependent variable. This new edition also allows readers to learn the basic and most commonly applied statistical techniques in business in an interactive way -- when using the web version -- through interactive Excel spreadsheets. All information has been revised to reflect Canadian content.

Subject:
Business and Finance
Mathematics
Statistics and Probability
Material Type:
Textbook
Provider:
BCcampus
Provider Set:
BCcampus Open Textbooks
Author:
Mohammad Mahbobi, Thompson Rivers University; Thomas K. Tiemann, Elon University
Date Added:
04/19/2016
Introductory Statistics
Unrestricted Use
CC BY
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0.0 stars

Introductory Statistics follows scope and sequence requirements of a one-semester introduction to statistics course and is geared toward students majoring in fields other than math or engineering. The text assumes some knowledge of intermediate algebra and focuses on statistics application over theory. Introductory Statistics includes innovative practical applications that make the text relevant and accessible, as well as collaborative exercises, technology integration problems, and statistics labs.

Subject:
Mathematics
Statistics and Probability
Material Type:
Textbook
Provider:
Rice University
Provider Set:
OpenStax College
Author:
Barbara Ilowsky
Susan Dean
Date Added:
07/19/2013
Introductory Statistics
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CC BY-NC-SA
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This book is meant to be a textbook for a standard one-semester introductory statistics course for general education students. Our motivation for writing it is twofold: 1.) to provide a low-cost alternative to many existing popular textbooks on the market; and 2.) to provide a quality textbook on the subject with a focus on the core material of the course in a balanced presentation.

Subject:
Mathematics
Statistics and Probability
Material Type:
Textbook
Provider:
The Saylor Foundation
Provider Set:
Saylor Textbooks
Author:
Douglas Shafer
Zhiyi Zhang
Date Added:
05/22/2019
Introductory Statistics with Randomization and Simulation First Edition
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CC BY-NC-SA
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We hope readers will take away three ideas from this book in addition to forming a foundation of statistical thinking and methods.

(1) Statistics is an applied field with a wide range of practical applications.

(2) You don't have to be a math guru to learn from interesting, real data.

(3) Data are messy, and statistical tools are imperfect. However, when you understand the strengths and weaknesses of these tools, you can use them to learn interesting things about the world.

Subject:
Mathematics
Statistics and Probability
Material Type:
Textbook
Provider:
OpenIntro
Author:
Christopher Barr
David Diez
Mine Çetinkaya-Runde
Date Added:
05/22/2019
Learning Objectives for Introductory Statistics
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CC BY-NC-SA
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This text document lists detailed learning objectives for introductory statistics courses. Learning objectives are brief, clear statements of what learners will be able to perform at the end of a course.

Subject:
Mathematics
Statistics and Probability
Material Type:
Activity/Lab
Provider:
Consortium for the Advancement of Undergraduate Statistics Education
Provider Set:
Causeweb.org
Author:
Jeff Thompson, Pam Arroway, Roger Woodard, North Carolina State University
Date Added:
05/23/2019
Learning R
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CC BY-SA
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0.0 stars

This resource was created at the University of Maryland (UMD) for instructors who want to teach, students (and instructors) who want to learn, and researchers who want to use R for statistical discovery and analysis. While this is a textbook, it is largely based on hands-on examples with video walk-throughs to take you through accessing R and RStudio, the basics of R and progressing to analyses with step by step templates and video support. The goal is to build confidence with programming early on and demonstrate best coding practices from the start.

Subject:
Applied Science
Computer Science
Mathematics
Statistics and Probability
Material Type:
Textbook
Author:
Dr. Amanda Chicoli
Emily Forgo
Dr. Tracy Tomlinson
Date Added:
03/24/2023
Math and Statistics Guides from UB’s Math & Statistics Center – Simple Book Publishing
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CC BY-NC-SA
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This book contains content originally posted to the Math Support Center Resources page, a blog run by student tutors and staff at the University of Baltimore. The chapters are mostly organized according to the tagging system of the source blog and may include references to specific math and statistics courses offered by the university.

Subject:
Algebra
Mathematics
Statistics and Probability
Material Type:
Activity/Lab
Data Set
Diagram/Illustration
Reading
Student Guide
Unit of Study
Author:
Jeremy Boettinger
Date Added:
05/10/2021
Mathematical Statistics, Spring 2016
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CC BY-NC-SA
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This course provides students with decision theory, estimation, confidence intervals, and hypothesis testing. It introduces large sample theory, asymptotic efficiency of estimates, exponential families, and sequential analysis.

Subject:
Mathematics
Statistics and Probability
Material Type:
Full Course
Provider:
M.I.T.
Provider Set:
M.I.T. OpenCourseWare
Author:
Peter Kempthorne
Date Added:
01/01/2016
Models, Data and Inference for Socio-Technical Systems, Spring 2007
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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:
M.I.T.
Provider Set:
M.I.T. OpenCourseWare
Author:
Frey, Daniel
Date Added:
01/01/2007
Mouse Experiment
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CC BY-NC-SA
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This Flash based applet simulates data from a case study of treatments for tumor growth in mice. This simulation allows the user to place mice into a control and treatment groups.

Subject:
Mathematics
Statistics and Probability
Material Type:
Activity/Lab
Provider:
Consortium for the Advancement of Undergraduate Statistics Education
Provider Set:
Causeweb.org
Author:
Dennis Pearl
Tom Santner
Date Added:
05/23/2019
Normal Distribution
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CC BY-NC-SA
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The applets in this section allow users to see how probabilities and quantiles are determined from a Normal distribution. For calculating probabilities, set the mean, variance, and limits; for calculating quantiles, set the mean, variance, and probability.

Subject:
Mathematics
Statistics and Probability
Material Type:
Activity/Lab
Provider:
Consortium for the Advancement of Undergraduate Statistics Education
Provider Set:
Causeweb.org
Author:
C. Anderson-Cook, S. Dorai-Raj, T. Robinson, Virginia Tech Department of Statistics
Date Added:
05/23/2019
Numerical Computation for Mechanical Engineers, Fall 2012
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CC BY-NC-SA
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This class introduces elementary programming concepts including variable types, data structures, and flow control. After an introduction to linear algebra and probability, it covers numerical methods relevant to mechanical engineering, including approximation (interpolation, least squares and statistical regression), integration, solution of linear and nonlinear equations, ordinary differential equations, and deterministic and probabilistic approaches. Examples are drawn from mechanical engineering disciplines, in particular from robotics, dynamics, and structural analysis. Assignments require MATLAB programming.

Subject:
Applied Science
Calculus
Engineering
Information Science
Mathematics
Statistics and Probability
Material Type:
Full Course
Provider:
M.I.T.
Provider Set:
M.I.T. OpenCourseWare
Author:
Anthony Patera
Daniel Frey
Nicholas Hadjiconstantinou
Date Added:
01/01/2012
OpenIntro Statistics
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CC BY-NC-ND
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0.0 stars

OpenIntro Statistics strives to be a complete introductory textbook of the highest caliber. Its core derives from the classic notions of statistics education and is extended by recent innovations. The textbook meets high quality standards and has been used at Princeton, Vanderbilt, UMass Amherst, and many other schools. We look forward to expanding the reach of the project and working with teachers from all colleges and schools.

Subject:
Mathematics
Statistics and Probability
Material Type:
Textbook
Provider:
OpenIntro
Author:
Christopher Barr
David Diez
Mine Cetinkaya-Rundel
Date Added:
01/01/2011
Parameters vs. Statistics
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LEARNING OBJECTIVE: Identify and distinguish between a parameter and a statistic.

LEARNING OBJECTIVE: Explain the concepts of sampling variability and sampling distribution.

Subject:
Mathematics
Statistics and Probability
Material Type:
Module
Provider:
Carnegie Mellon University
Provider Set:
Open Learning Initiative
Date Added:
05/22/2019