This textbook is an introduction to Psychology. It covers how psychologists think, principles of memory, learning, and thinking; human nature, human development, the social world, and wellbeing.

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.

  Introductory Statistics is a non-calculus based, descriptive statistics course with applications. Topics include methods of collecting, organizing, and interpreting data; measures of central tendency, position, and variability for grouped and ungrouped data; frequency distributions and their graphical representations; introduction to probability theory, standard normal distribution, and areas under the curve. Course materials created by Fahmil Shah, content added to OER Commons by Victoria Vidal.

  Introductory Statistics is a non-calculus based, descriptive statistics course with applications. Topics include methods of collecting, organizing, and interpreting data; measures of central tendency, position, and variability for grouped and ungrouped data; frequency distributions and their graphical representations; introduction to probability theory, standard normal distribution, and areas under the curve. Course materials created by Fahmil Shah, content added to OER Commons by Victoria Vidal.

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.

Susan Dean and Barbara Illowsky (Published 2013 by OpenStax College)
Adapted by: College of Lake County Faculty: Riyanti Boyd and Natalia Casper
Revised July 2021

This project was funded by a grant from the College of Lake County Foundation.
Adapted College of Lake County text can be found at:
http://dept.clcillinois.edu/mth/oer/IntroductoryStatistics.pdf

Original text materials for Introductory Statistics by Dean and Illowski 2013
available at: http://cnx.org/content/col11562/latest/.

Original Publication Under the following license:

This work is licensed under the
Creative Commons Attribution-Noncommercial-Share Alike 3.0 unported license.
To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/3.0/
or send a letter to Creative Commons, 171 Second Street, Suite 300, San Francisco,
California, 94105, USA.

  Introductory Statistics is a non-calculus based, descriptive statistics course with applications. Topics include methods of collecting, organizing, and interpreting data; measures of central tendency, position, and variability for grouped and ungrouped data; frequency distributions and their graphical representations; introduction to probability theory, standard normal distribution, and areas under the curve. Course materials created by Fahmil Shah, content added to OER Commons by Victoria Vidal.

  Introductory Statistics is a non-calculus based, descriptive statistics course with applications. Topics include methods of collecting, organizing, and interpreting data; measures of central tendency, position, and variability for grouped and ungrouped data; frequency distributions and their graphical representations; introduction to probability theory, standard normal distribution, and areas under the curve. Course materials created by Fahmil Shah, content added to OER Commons by Victoria Vidal.

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.

This video covers an introduction and explanation of Expected Value and how to calculate it.

Learning Statistics with R covers the contents of an introductory statistics class, as typically taught to undergraduate psychology students, focusing on the use of the R statistical software. The book discusses how to get started in R as well as giving an introduction to data manipulation and writing scripts.

"Rising textbook costs are a potential barrier to student progression and retention. Therefore, a group of faculty in the department of Mathematics at Augusta University has decided to adopt an open textbook for use in an Elementary Statistics course.

We have developed a set of materials to accompany the OpenStax Introductory Statistics textbook by Illowsky and Dean including lecture/study notes and projects.

These materials are meant as a supplement for teachers and learners who are using the OpenStax Introductory Statistics textbook by Illowsky and Dean. These materials also incorporate the use of other technologies (R and Excel) in an open statistics course for students and instructors who wish to use technologies other than the TI-83/84 graphing calcuator."

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.

This course materials are for General Education course Introduction to Statistics. The contents include data collection, frequency distributions, probability and probability distributions, sampling and sampling distributions, hypothesis testing with applications in various fields, regression and correlation analysis.

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.

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.

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.

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.

This is a course design utilizing Mostly Harmless Statistics by Rachel L. Webb.© 2021, Originally published in 2019This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.   Publication of this OER guide was made possible by Portland State University Library PDXOpen Publishing Initiative Grant program.  Persistent Identifier:  https://archives.pdx.edu/ds/psu/36164   Webb, Rachel, "Mostly Harmless Statistics" (2021). PDXOpen: Open Educational Resources. 36.https://pdxscholar.library.pdx.edu/pdxopen/36  

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.