Elementary Statistics and Probability
Elementary Statistics and Probability
Introductory Statistics
Common Course ID: MATH 110
CCC Instructor Open Textbook Adoption Portrait
Abstract: This open textbook is being utilized in an introductory statistics course for undergraduate students not majoring in science or math by Barbara Illowsky, Ph.D at De Anza College in Northern California. The open textbook focuses on the application of statistical knowledge rather than the theory behind it. The main motivation to adopt an open textbook was to save the students money. Most students access the open textbook online in the web format.
Reviews: The book has been reviewed by a CCC faculty member,a CSU faculty member and a UC faculty from within the California higher education system. There is also an Accessibility Evaluation.
About the Textbook
sticsDescription:
This introductory, one-semester textbook is geared towards students who are not majoring in math and science and 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, which has been widely adopted. This new version has enhancements in artwork, terminology, and practical applications to enhance the relevance and accessibility for students. The text also includes collaborative exercises, integration with TI-83, 83+, 84+ calculators, technology integration problems, and statistics labs.
Authors:
- Susan Dean, De Anza College, California
- Barbara Illowsky, Ph.D., De Anza College, California
Formats:
This book is available online and as a PDF and Bookshare. You can also purchase a print copy for $33.50.
Supplemental Resources:
- Online homework tools and interactive study guides for students and faculty provided.
- Faculty-only resources such as solutions and slides are also available.
Peer Reviews:
The book has been reviewed by a CCC faculty member,a CSU faculty member and a UC faculty from within the California higher education system. There is also an Accessibility Evaluation.
Cost Savings:
Students can experience significant savings depending on previous textbook selections. Purchasing a new traditional textbook, Prem S. Mann's Introductory Statististics, published by Wiley and Sons costs over $150 at Amazon.com. The free online Introductory Statistics from OpenStax College is also available in a print version for about $34 plus shipping and handling.
Accessibility and Diversity Statement from Publisher:
Not all formats of the textbook have been evaluated, but the most recent version of this open textbook is available in a Bookshare format which supports DAISY and Braille-Ready-Format (BRF).
License:
Except where otherwise noted, Introductory Statistics by OpenStax College is licensed under a Creative Commons Attribution 3.0 Unported License. This license lets others distribute, remix, tweak, and build upon the work, even commercially, as long as they credit the author for the original creation. This is the most accommodating of licenses offered. Recommended for maximum dissemination and use of licensed materials.
About the Course
Math 10:
Elementary Statistics and Probability
Description:
Introduction to data analysis making use of graphical and numerical techniques to study patterns. Emphasis on understanding variation, collects information in the face of uncertainty, checks distributional assumptions, tests hypotheses, uses probability as a tool for anticipating what the distribution of data may look like under a set of assumptions, and uses appropriate statistical models to draw conclusions. The course introduces the student to applications in engineering, business, economics, medicine, education, the sciences, and those pertaining to issues of contemporary interest. The use of technology (computers or graphing calculators) will be required in certain applications.
Prerequisite: Intermediate Algebra or Math 114
GE Credit: 5 units; Degree applicable.
- Organize, analyze, and utilize appropriate methods to draw conclusions based on sample data by constructing and/or evaluating tables, graphs, and numerical measures characteristics of data.
- Identify, evaluate, interpret and describe data distributions through the study of sampling distributions and probability theory.
- Collect data, interpret, compose and defend conjectures, and communicate the results of random data using statistical analysis such as interval and point estimates, hypothesis tests, and regression analysis.
Curricular Changes: None
Teaching and Learning Impact:
- More faculty collaboration: Yes
- Wider range of teaching materials: Online homework
- Student learning improved: Unknown
- Student retention improved: Unknown
- Any unexpected results: None
Sample Assignments and Syllabus:
The Normal Distribution Lab
The student will compare empirical data and a theoretical distribution to determine if everyday experiment fits a continuous distribution.
Textbook Adoption
OER Adoption Process
Susan Dean and I originally wrote this textbook to incorporate technology such as calculators into the statistics curriculum to make it more relevant to today's students. When the textbook became openly licensed, we worked with the college bookstore to provide hard copies that students could purchase if desired.
Student Access:
I encourage the students to use the text exclusively online. About half the students prefer the hardcopy and purchase that version for approximately $34.00 either through the bookstore or OpenStax College.
Student Feedback or Participation:
Students express deep appreciation for the free and low-cost options. Students from across the world have thanked me for the iTunesU free videos which they use to supplement their own courses with other texts.
The Liberation of Textbooks
Case study of a De Anza College student and the impact of open textooks on her budget.
Barbara Illowsky, Ph.D
I teach developmental mathematics and lower-division statistics and mathematics courses. I believe that the instructor’s role is to enable students to achieve their goals and instill a desire for lifelong learning.