Collaborative Statistics

Collaborative Statistics was written by Barbara Illowsky and Susan Dean, faculty members at De Anza College in Cupertino, California. The textbook was developed over several years and has been used in regular and honors-level classroom settings and in distance learning classes. Courses using this textbook have been articulated by the University of California for transfer of credit. The textbook contains full materials for course offerings, including expository text, examples, labs, homework, and projects. A Teacher’s Guide is currently available in print form and on the Connexions site at and supplemental course materials including additional problem sets and video lectures are available. The on-line text for each of these collections collections will meet the Section 508 standards for accessibility.

An on-line course based on the textbook was also developed by Illowsky and Dean. It has won an award as the best on-line California community college course. The on-line course will be available at a later date as a collection in Connexions, and each lesson in the on-line course will be linked to the on-line textbook chapter. The on-line course will include, in addition to expository text and examples, videos of course lectures in captioned and non-captioned format.

The original preface to the book as written by professors Illowsky and Dean, now follows:

This book is intended for introductory statistics courses being taken by students at two– and four–year colleges who are majoring in fields other than math or engineering. Intermediate algebra is the only prerequisite. The book focuses on applications of statistical knowledge rather than the theory behind it. The text is named Collaborative Statistics because students learn best by doing. In fact, they learn best by working in small groups. The old saying “two heads are better than one” truly applies here.

Our emphasis in this text is on four main concepts:

thinking statistically

incorporating technology

working collaboratively

writing thoughtfully

These concepts are integral to our course. Students learn the best by actively participating, not by just watching and listening. Teaching should be highly interactive. Students need to be thoroughly engaged in the learning process in order to make sense of statistical concepts. Collaborative Statistics provides techniques for students to write across the curriculum, to collaborate with their peers, to think statistically, and to incorporate technology.

This book takes students step by step. The text is interactive. Therefore, students can immediately apply what they read. Once students have completed the process of problem solving, they can tackle interesting and challenging problems relevant to today’s world. The problems require the students to apply their newly found skills. In addition, technology (TI-83 graphing calculators are highlighted) is incorporated throughout the text and the problems, as well as in the special group activities and projects. The book also contains labs that use real data and practices that lead students step by step through the problem solving process.

At De Anza, along with hundreds of other colleges across the country, the college audience involves a large number of ESL students as well as students from many disciplines. The ESL students, as well as the non-ESL students, have been especially appreciative of this text. They find it extremely readable and understandable. Collaborative Statistics has been used in classes that range from 20 to 120 students, and in regular, honor, and distance learning classes.

An on-line course based on the textbook was also developed by Illowsky and Dean. It has won an award as the best on-line California community college course. The on-line course will be available at a later date as a collection in Connexions, and each lesson in the on-line course will be linked to the on-line textbook chapter. The on-line course will include, in addition to expository text and examples, videos of course lectures in captioned and non-captioned format.

The original preface to the book as written by professors Illowsky and Dean, now follows:

This book is intended for introductory statistics courses being taken by students at two– and four–year colleges who are majoring in fields other than math or engineering. Intermediate algebra is the only prerequisite. The book focuses on applications of statistical knowledge rather than the theory behind it. The text is named Collaborative Statistics because students learn best by doing. In fact, they learn best by working in small groups. The old saying “two heads are better than one” truly applies here.

Our emphasis in this text is on four main concepts:

thinking statistically

incorporating technology

working collaboratively

writing thoughtfully

These concepts are integral to our course. Students learn the best by actively participating, not by just watching and listening. Teaching should be highly interactive. Students need to be thoroughly engaged in the learning process in order to make sense of statistical concepts. Collaborative Statistics provides techniques for students to write across the curriculum, to collaborate with their peers, to think statistically, and to incorporate technology.

This book takes students step by step. The text is interactive. Therefore, students can immediately apply what they read. Once students have completed the process of problem solving, they can tackle interesting and challenging problems relevant to today’s world. The problems require the students to apply their newly found skills. In addition, technology (TI-83 graphing calculators are highlighted) is incorporated throughout the text and the problems, as well as in the special group activities and projects. The book also contains labs that use real data and practices that lead students step by step through the problem solving process.

At De Anza, along with hundreds of other colleges across the country, the college audience involves a large number of ESL students as well as students from many disciplines. The ESL students, as well as the non-ESL students, have been especially appreciative of this text. They find it extremely readable and understandable. Collaborative Statistics has been used in classes that range from 20 to 120 students, and in regular, honor, and distance learning classes.

Barbara Illowsky

Susan Dean

OpenStax CNX

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Natural Resources Biometrics

Natural Resources Biometrics begins with a review of descriptive statistics, estimation, and hypothesis testing. The following chapters cover one- and two-way analysis of variance (ANOVA), including multiple comparison methods and interaction assessment, with a strong emphasis on application and interpretation. Simple and multiple linear regressions in a natural resource setting are covered in the next chapters, focusing on correlation, model fitting, residual analysis, and confidence and prediction intervals. The final chapters cover growth and yield models, volume and biomass equations, site index curves, competition indices, importance values, and measures of species diversity, association, and community similarity.

Diane Kiernan

Open SUNY Textbooks

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Introductory Business Statistics with Interactive Spreadsheets

Introductory Business Statistics with Interactive Spreadsheets – 1st Canadian Edition is an adaptation of Thomas K. Tiemann’s book, Introductory Business Statistics. This new edition still contains the basic ideas behind statistics, such as populations, samples, the difference between data and information, and sampling distributions as well as information on descriptive statistics and frequency distributions, normal and t-distributions, hypothesis testing, t-tests, f-tests, analysis of variance, non-parametric tests, and regression basics. New topics include 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. For each topic, a customized interactive template has been created within which selected values can be repeatedly changed to observe how the entire process, as well as the outcomes, are automatically adjusted.

Also, in this adapted edition, the real-world examples throughout the text, and the information in general, have been revised to reflect Canadian content.

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. For each topic, a customized interactive template has been created within which selected values can be repeatedly changed to observe how the entire process, as well as the outcomes, are automatically adjusted.

Also, in this adapted edition, the real-world examples throughout the text, and the information in general, have been revised to reflect Canadian content.

Thomas K. Tiemann

Mohammad Mahbobi

BCcampus

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Probability and Statistics

We discuss probability and do some basic examples to refresh our memory on practice problems involving probability. Next video we focus on expectation values/ mean and the second moment of distribution.

http://youtu.be/Ky2DfnDbV-k

SciencewithGurni !

published via YouTube.com

published via YouTube.com

2017-09-01T03:04:12.000Z

https://i.ytimg.com/vi/Ky2DfnDbV-k/default.jpg

Statistical Mechanics

This is a book about statistical mechanics at the advanced undergraduate level. It assumes a background in

classical mechanics through the concept of phase space, in quantum mechanics through the Pauli exclusion

principle, and in mathematics through multivariate calculus. (Section 9.2 also assumes that you can can

diagonalize a 2 x 2 matrix.)

classical mechanics through the concept of phase space, in quantum mechanics through the Pauli exclusion

principle, and in mathematics through multivariate calculus. (Section 9.2 also assumes that you can can

diagonalize a 2 x 2 matrix.)

Daniel F. Styer

http://www2.oberlin.edu/physics/dstyer/StatMech/book.pdf

Rahmah Agustira

Creative Commons

Introductory Statistics

ntroductory Statistics is designed for the one-semester, introduction to statistics course and is geared toward students majoring in fields other than math or engineering. This text assumes students have been exposed to intermediate algebra, and it focuses on the applications of statistical knowledge rather than the theory behind it. The foundation of this textbook is Collaborative Statistics, by Barbara Illowsky and Susan Dean. Additional topics, examples, and ample opportunities for practice have been added to each chapter. The development choices for this textbook were made with the guidance of many faculty members who are deeply involved in teaching this course. These choices led to innovations in art, terminology, and practical applications, all with a goal of increasing relevance and accessibility for students. We strove to make the discipline meaningful, so that students can draw from it a working knowledge that will enrich their future studies and help them make sense of the world around them.

OpenStax College

https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=10&cad=rja&uact=8&ved=0ahUKEwiP8cmZ4b3YAhUNTo8KHR5oBzsQFghTMAk&url=https%3A%2F%2Fcnx.org%2Fexports%2Fb56bb9e9-5eb8-48ef-9939-88b1b12ce22f%4021.6.pdf%2Fintroductory-statistics-21.6.pdf&usg=AOvVaw2_hIEFVG56Q8D46QfkcADi

Rice University

Rahmah Agustira

Creative Commons

OpenIntro Statistics

The OpenIntro project was founded in 2009 to improve the quality and availability of education by producing exceptional books and teaching tools that are free to use and easy to modify. The inaugural effort is OpenIntro Statistics. Probability is optional, inference is key, and we feature real data whenever possible.

License: Creative Commons Attribution Sharealike. This license is considered to be some to be the most open license. It allows reuse, remixing, and distribution (including commercial), but requires any remixes use the same license as the original. This limits where the content can be remiThe OpenIntro project was founded in 2009 to improve the quality and availability of education by producing exceptional books and teaching tools that are free to use and easy to modify. The inaugural effort is OpenIntro Statistics. Probability is optional, inference is key, and we feature real data whenever possible.

License: Creative Commons Attribution Sharealike. This license is considered to be some to be the most open license. It allows reuse, remixing, and distribution (including commercial), but requires any remixes use the same license as the original. This limits where the content can be remixed into, but on the other hand ensures that no-one can remix the content then put the remix under a more restrictive license.xed into, but on the other hand ensures that no-one can remix the content then put the remix under a more restrictive license.

License: Creative Commons Attribution Sharealike. This license is considered to be some to be the most open license. It allows reuse, remixing, and distribution (including commercial), but requires any remixes use the same license as the original. This limits where the content can be remiThe OpenIntro project was founded in 2009 to improve the quality and availability of education by producing exceptional books and teaching tools that are free to use and easy to modify. The inaugural effort is OpenIntro Statistics. Probability is optional, inference is key, and we feature real data whenever possible.

License: Creative Commons Attribution Sharealike. This license is considered to be some to be the most open license. It allows reuse, remixing, and distribution (including commercial), but requires any remixes use the same license as the original. This limits where the content can be remixed into, but on the other hand ensures that no-one can remix the content then put the remix under a more restrictive license.xed into, but on the other hand ensures that no-one can remix the content then put the remix under a more restrictive license.

Diez, Barr

Cetinkaya-Rundel

http://www.opentextbookstore.com/details.php?id=12

Cut Rita Zahara

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Foundations in Statistical Reasoning

This book starts by presenting an overview of the statistical thought process. By the end of chapter 2, students are already familiar with concepts such as hypotheses, level of significance, p-values, errors. Normally these topics are not introduced until after a discussion of probability and sampling distributions. My approach to probability and sampling distributions is also very different. Because students using this book know about hypotheses before we reach the probability section, inferential theory can be developed by applying the probability rules the testing of a hypothesis. To me, this leads to better and more interesting questions than are typically asked in these sections and gives meaning to these concepts. Other differences include homework problems that require the integration of topics from different chapters as well as one problem in each chapter based on issues discussed in other classes on our campus (e.g. psychology, criminal justice, economics, etc).

Pete Kaslik

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pdf file