# All resources in OpenStax Introductory Statistics

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This collection of spreadsheet-based labs was funded as part of the Digital Learning Research Network (dLRN) made possible by a grant from the Bill and Melinda Gates Foundation. The labs were adapted from the Statistics book, “Introduction to Statistics,” published by OpenStax College. The original labs used graphing calculators and were found within the book after each chapter. These interactive spreadsheet-based labs are effective for online and face-face courses. They may also be used with the book (see Resource: Lab Mapping to Book Chapters) or stand-alone.Authors: Barbara Illowsky PhD, Foothill-De Anza Community College District; Larry Green PhD, Lake Tahoe Community College; James Sullivan, Sierra College; Lena Feinman,College of San Mateo; Cindy Moss, Skyline College; Sharon Bober, Pasadena Community College; Lenore Desilets, De Anza Community College.Lab Mapping to Book ChaptersGrading RubricLabsUnivariarate Data Normal DistributionCentral Limit TheoremHyporhesis Test - Single MeanHyporhesis Test - Single ProportionGoodness of FitLinear Regression

Material Type: Module

Authors: lenore desilets, Barbara Illowsky

# Introduction to Statistics

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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)

Material Type: Full Course

# OER & Online Learning: Faculty Quick Start Guide

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The Faculty Quick Start Guide is an outcome of a project by ISKME, supported by a grant from the Michelson 20MM Foundation, to conduct a study and develop a set of resources to accelerate OER use for distance education, especially the urgent shift to remote learning during the pandemic in 2020. The Guide, created in collaboration with a selection of OER and online education champions across California community colleges (CCC), contains: - Models and approaches to online learning, and to emergency remote learning in the context of COVID-19; - How and to what extent OER fits into these models, and local and state-level supports needed for its integration and sustainability; - Design considerations for integrating OER in online learning, including pedagogical and platform considerations; - Curatorial practices, such as using OER curation tools and aligning curated OER to learning outcomes; and, - Starting points and tips for colleges and faculty who want to initiate OER integration into distance education. Tailored to faculty and campus administrators both in California and beyond, the Guide has the aim is to enable system-wide shifts to meet postsecondary institutions’ long term goals for distance learning, and faculty’s emergency plans for remote learning in response to the COVID-19 and potential future crises. The Guide is also available as a PDF for download: https://drive.google.com/file/d/17AXs30dZeLOrGeNBQ-ISc_OJXIxE9xtB/view?usp=sharing. See the companion guide for administrators at: https://www.oercommons.org/courses/iskme-michelson-20mm-oer-campus-administrator-quick-start-guide-public/edit

Author: ISKME

# MTH 243 Supplement to OpenStax Statistics

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This supplement is designed for MTH 243 at Portland Community College and is used in conjunction with OpenStax Statistics: https://openstax.org/details/introductory-statistics

Material Type: Activity/Lab

Authors: Emiliano Vega, Ralf Youtz

# Introductory Statistics

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Introductory Statistics is intended for the one-semester introduction to statistics course for students who are not mathematics or engineering majors. It focuses on the interpretation of statistical results, especially in real world settings, and assumes that students have an understanding of intermediate algebra. In addition to end of section practice and homework sets, examples of each topic are explained step-by-step throughout the text and followed by a Try It problem that is designed as extra practice for students. This book also includes collaborative exercises and statistics labs designed to give students the opportunity to work together and explore key concepts. While the book has been built so that each chapter builds on the previous, it can be rearranged to accommodate any instructor’s particular needs.

Material Type: Textbook

Author: Alexander Holmes

# Online Statistics: An Interactive Multimedia Course of Study

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Online Statistics: An Interactive Multimedia Course of Study is an introductory-level statistics book. The material is presented both as a standard textbook and as a multimedia presentation. The book features interactive demonstrations and simulations, case studies, and an analysis lab.

Material Type: Case Study, Full Course, Simulation, Textbook

Author: David Lane

# Probability and Statistics EBook

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This is an Internet-based probability and statistics E-Book. The materials, tools and demonstrations presented in this E-Book would be very useful for advanced-placement (AP) statistics educational curriculum. The E-Book is initially developed by the UCLA Statistics Online Computational Resource (SOCR). However, all statistics instructors, researchers and educators are encouraged to contribute to this project and improve the content of these learning materials. There are 4 novel features of this specific Statistics EBook. It is community-built, completely open-access (in terms of use and contributions), blends information technology, scientific techniques and modern pedagogical concepts, and is multilingual.

Material Type: Textbook

# Passion-Driven Statistics ebook

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Here is the link to the new Passion-Driven Statistics e-book! Github book https://bit.ly/PDSe-book pdf version https://bit.ly/PDSpdf Passion-Driven Statistics is an NSF-funded, multidisciplinary, project-based curriculum that supports students in conducting data-driven research, asking original questions, and communicating methods and results using the language of statistics. The curriculum supports students to work with existing data covering psychology, health, earth science, government, business, education, biology, ecology and more. From existing data, students are able to pose questions of personal interest and then use statistical software (e.g. SAS, R, Python, Stata, SPSS) to answer them. The e-book is presented in pdf format for ease of use across platforms. http://bit.ly/EditPDSe-book For more information, contact Lisa Dierker, ldierker@wesleyan.edu or check out the Passion-Driven Statistics website at https://passiondrivenstatistics.com/

Material Type: Activity/Lab, Full Course, Homework/Assignment, Lesson Plan, Textbook

Authors: Kristin Flaming, Lisa Dierker

# OpenStax Statistics Chapter 2 Lecture Notes

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PowerPoint Slides to accompany Chapter 2 of OpenStax Statistics textbook. Prepared by River Parishes Community College (Jared Eusea, Assistant Professor of Mathematics, and Ginny Bradley, Instructor of Mathematics) for OpenStax Statistics textbook under a Creative Commons Attribution-ShareAlike 4.0 International License. Date provided: July 2019.

Material Type: Lecture, Lecture Notes

Author: Jared Eusea

# OpenStax Statistics Chapter 3 Lecture Notes

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PowerPoint Slides to accompany Chapter 3 of OpenStax Statistics textbook. Prepared by River Parishes Community College (Jared Eusea, Assistant Professor of Mathematics, and Ginny Bradley, Instructor of Mathematics) for OpenStax Statistics textbook under a Creative Commons Attribution-ShareAlike 4.0 International License. Date provided: July 2019.

Material Type: Lecture, Lecture Notes

Author: Jared Eusea

# OpenStax Introduction to Statistics Problem Sets

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Test, quiz, and assignment problem sets that go with the OpenStax Introduction to Statistics Textbook

Material Type: Homework/Assignment

Authors: Alex Jordan, Tien Chih

# OpenStax Introductory Statistics Videos with Lecture Power Points and Additional Notes

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This resource is a collection of short closed-captioned lectures that accompany the power points covering most of chapters 1,2,3, 6, 9, 11, 12, and 13 of the OpenStax Introductory Statistics book. The Power Points are provided in both .PPT and .PDF format to accommodate downloading ease. The notes are in .DOC format.

Material Type: Full Course, Lecture

Author: Camille Pace

# OpenStax Statistics Chapter 6 Lecture Notes

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PowerPoint Slides to accompany Chapter 6 of OpenStax Statistics textbook. Prepared by River Parishes Community College (Jared Eusea, Assistant Professor of Mathematics, and Ginny Bradley, Instructor of Mathematics) for OpenStax Statistics textbook under a Creative Commons Attribution-ShareAlike 4.0 International License. Date provided: July 2019.

Material Type: Lecture, Lecture Notes

Author: Jared Eusea

# OpenStax Statistics Chapter 4 Lecture Notes

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PowerPoint Slides to accompany Chapter 4 of OpenStax Statistics textbook. Prepared by River Parishes Community College (Jared Eusea, Assistant Professor of Mathematics, and Ginny Bradley, Instructor of Mathematics) for OpenStax Statistics textbook under a Creative Commons Attribution-ShareAlike 4.0 International License. Date provided: July 2019.

Material Type: Lecture, Lecture Notes

Author: Jared Eusea

# OpenStax Statistics Chapter 7 Lecture Notes

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PowerPoint Slides to accompany Chapter 7 of OpenStax Statistics textbook. Prepared by River Parishes Community College (Jared Eusea, Assistant Professor of Mathematics, and Ginny Bradley, Instructor of Mathematics) for OpenStax Statistics textbook under a Creative Commons Attribution-ShareAlike 4.0 International License. Date provided: July 2019.

Material Type: Lecture, Lecture Notes

Author: Jared Eusea

# OpenStax Statistics Chapter 8 Lecture Notes

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PowerPoint Slides to accompany Chapter 8 of OpenStax Statistics textbook. Prepared by River Parishes Community College (Jared Eusea, Assistant Professor of Mathematics, and Ginny Bradley, Instructor of Mathematics) for OpenStax Statistics textbook under a Creative Commons Attribution-ShareAlike 4.0 International License. Date provided: July 2019.

Material Type: Lecture, Lecture Notes

Author: Jared Eusea

# OpenStax Statistics Chapter 9 Lecture Notes

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PowerPoint Slides to accompany Chapter 9 of OpenStax Statistics textbook. Prepared by River Parishes Community College (Jared Eusea, Assistant Professor of Mathematics, and Ginny Bradley, Instructor of Mathematics) for OpenStax Statistics textbook under a Creative Commons Attribution-ShareAlike 4.0 International License. Date provided: July 2019.

Material Type: Lecture, Lecture Notes

Author: Jared Eusea

# OpenStax Statistics Chapter 1 Lecture Notes

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PowerPoint Slides to accompany Chapter 1 of OpenStax Statistics textbook. Prepared by River Parishes Community College (Jared Eusea, Assistant Professor of Mathematics, and Ginny Bradley, Instructor of Mathematics) for OpenStax Statistics textbook under a Creative Commons Attribution-ShareAlike 4.0 International License. Date provided: July 2019.

Material Type: Lecture, Lecture Notes

Author: Jared Eusea

# College Trigonometry

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This book was designed as an introductory trigonometry textbook for college students with the explicit goal of reducing textbook costs.

Material Type: Textbook

Authors: Carl Stitz, Jeff Zeager