25/05/2018, 16:07

Introductory 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 ...

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.

Coverage and Scope

Chapter 1 Sampling and Data
Chapter 2 Descriptive Statistics
Chapter 3 Probability Topics
Chapter 4 Discrete Random Variables
Chapter 5 Continuous Random Variables
Chapter 6 The Normal Distribution
Chapter 7 The Central Limit Theorem
Chapter 8 Confidence Intervals
Chapter 9 Hypothesis Testing with One Sample
Chapter 10 Hypothesis Testing with Two Samples
Chapter 11 The Chi-Square Distribution
Chapter 12 Linear Regression and Correlation
Chapter 13 F Distribution and One-Way ANOVA

Alternate Sequencing

was conceived and written to fit a particular topical sequence, but it can be used flexibly to accommodate other course structures. One such potential structure, which will fit reasonably well with the textbook content, is provided. Please consider, however, that the chapters were not written to be completely independent, and that the proposed alternate sequence should be carefully considered for student preparation and textual consistency.

Chapter 1 Sampling and Data
Chapter 2 Descriptive Statistics
Chapter 12 Linear Regression and Correlation
Chapter 3 Probability Topics
Chapter 4 Discrete Random Variables
Chapter 5 Continuous Random Variables
Chapter 6 The Normal Distribution
Chapter 7 The Central Limit Theorem
Chapter 8 Confidence Intervals
Chapter 9 Hypothesis Testing with One Sample
Chapter 10 Hypothesis Testing with Two Samples
Chapter 11 The Chi-Square Distribution
Chapter 13 F Distribution and One-Way ANOVA

Pedagogical Foundation and Features

  • Examples are placed strategically throughout the text to show students the step-by-step process of interpreting and solving statistical problems. To keep the text relevant for students, the examples are drawn from a broad spectrum of practical topics; these include examples about college life and learning, health and medicine, retail and business, and sports and entertainment.
  • Try It practice problems immediately follow many examples and give students the opportunity to practice as they read the text. They are usually based on practical and familiar topics, like the Examples themselves.
  • Collaborative Exercises provide an in-class scenario for students to work together to explore presented concepts.
  • Using the TI-83, 83+, 84, 84+ Calculator shows students step-by-step instructions to input problems into their calculator.
  • The Technology Icon indicates where the use of a TI calculator or computer software is recommended.
  • Practice, Homework, and Bringing It Together problems give the students problems at various degrees of difficulty while also including real-world scenarios to engage students.

Statistics Labs

These innovative activities were developed by Barbara Illowsky and Susan Dean in order to offer students the experience of designing, implementing, and interpreting statistical analyses. They are drawn from actual experiments and data-gathering processes, and offer a unique hands-on and collaborative experience. The labs provide a foundation for further learning and classroom interaction that will produce a meaningful application of statistics.

Statistics Labs appear at the end of each chapter, and begin with student learning outcomes, general estimates for time on task, and any global implementation notes. Students are then provided step-by-step guidance, including sample data tables and calculation prompts. The detailed assistance will help the students successfully apply the concepts in the text and lay the groundwork for future collaborative or individual work.

Ancillaries

  • Instructor’s Solutions Manual
  • Webassign Online Homework System
  • Video Lectures delivered by Barbara Illowsky are provided for each chapter.

Senior Contributing Authors

Barbara Illowsky De Anza College
Susan Dean De Anza College

Contributors

Abdulhamid Sukar Cameron University
Abraham Biggs Broward Community College
Adam Pennell Greensboro College
Alexander Kolovos
Andrew Wiesner Pennsylvania State University
Ann Flanigan Kapiolani Community College
Benjamin Ngwudike Jackson State University
Birgit Aquilonius West Valley College
Bryan Blount Kentucky Wesleyan College
Carol Olmstead De Anza College
Carol Weideman St. Petersburg College
Charles Ashbacher Upper Iowa University, Cedar Rapids
Charles Klein De Anza College
Cheryl Wartman University of Prince Edward Island
Cindy Moss Skyline College
Daniel Birmajer Nazareth College
David Bosworth Hutchinson Community College
David French Tidewater Community College
Dennis Walsh Middle Tennessee State University
Diane Mathios De Anza College
Ernest Bonat Portland Community College
Frank Snow De Anza College
George Bratton University of Central Arkansas
Inna Grushko De Anza College
Janice Hector De Anza College
Javier Rueda De Anza College
Jeffery Taub Maine Maritime Academy
Jim Helmreich Marist College
Jim Lucas De Anza College
Jing Chang College of Saint Mary
John Thomas College of Lake County
Jonathan Oaks Macomb Community College
Kathy Plum De Anza College
Larry Green Lake Tahoe Community College
Laurel Chiappetta University of Pittsburgh
Lenore Desilets De Anza College
Lisa Markus De Anza College
Lisa Rosenberg Elon University
Lynette Kenyon Collin County Community College
Mark Mills Central College
Mary Jo Kane De Anza College
Mary Teegarden San Diego Mesa College
Matthew Einsohn Prescott College
Mel Jacobsen Snow College
Michael Greenwich College of Southern Nevada
Miriam Masullo SUNY Purchase
Mo Geraghty De Anza College
Nydia Nelson St. Petersburg College
Philip J. Verrecchia York College of Pennsylvania
Robert Henderson Stephen F. Austin State University
Robert McDevitt Germanna Community College
Roberta Bloom De Anza College
Rupinder Sekhon De Anza College
Sara Lenhart Christopher Newport University
Sarah Boslaugh Kennesaw State University
Sheldon Lee Viterbo University
Sheri Boyd Rollins College
Sudipta Roy Kankakee Community College
Travis Short St. Petersburg College
Valier Hauber De Anza College
Vladimir Logvenenko De Anza College
Wendy Lightheart Lane Community College
Yvonne Sandoval Pima Community College

Sample TI Technology

Disclaimer: The original calculator image(s) by Texas Instruments, Inc. are provided under CC-BY. Any subsequent modifications to the image(s) should be noted by the person making the modification. (Credit: ETmarcom TexasInstruments)
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