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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.

About our team

Senior contributing authors

Barbara Illowsky De Anza College
Susan Dean De Anza College

Contributing authors

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

calculators
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)

Questions & Answers

2. The data that categories patients as males or females are known
shivani Reply
20 25 find the area under the normal curve
Akram Reply
find the area normal curve
Akram
Let x1, x2, ...,xn be a random sample of size n from N(0,σ  ), show that there exists an UMP test with significance level α for testing H0 :  2 =  2 against H1 :  2 <  2 . If n=15,  = 0.05, and  2= 3, determine the BCR
Bhavana Reply
explain null and alternative hypothesis are formulated
Shams
please give me reply quickly
Shams
3xy^2√[x^3y^2/(12(x^3y)^2)]
Esther Reply
what is probability
Esther
what is probability
Esther
what is probability
Esther
Probability is a branch of mathematics that deals with the occurrence of a random event. For example, when a coin is tossed in the air, the possible outcomes are Head and Tail.
Dewan
explain null and alternative hypothesis are farmulated
Shams
please give answer quickly
Shams
quick
Shams
mean 0 and standard deviation 1 .using area table find P(X>3)
Naeem Reply
hi
Shams
what is terms data?
Mohsin Reply
define the types of data?
Mohsin
define the number of classes?
Mohsin
define the class limt?
Mohsin
define the class frequency and class interval ?
Mohsin
define class boundaries
George
Your home address nominal Interval ratio ordinal
MD
home address is nominal
Awel
what is axioms of probability
Khaleed Reply
characteristics of statistic
Safi Reply
a measure of cntral tendency is a quantitative value that tends to locate in some sense the middle of a set of data
khan Reply
in a large metropolitan area
Vernon Reply
a lecturer claims that his students score an average of 55 marks in their statistics test. the object supervisor wants to know wether the lecturer's claims is acceptable or not.what is the posible tail of the test?
Karen
2
J-zil
the best sampling method for A school has a total of 100 teachers. Each teacher in the school is given a number and then a random sample of 35 teachers is obtained.
Nurhaznissah Reply
what the best sampling method for A school has a total of 100 teachers. Each teacher in the school is given a number and then a random sample of 35 teachers is obtained.
Nurhaznissah
option please
Dewan
systematic
Dewan
any one send me the notes of these chpt if possible introduction to statistics measure of centeral tendency or average measure of dispensation moments and skewness presentation of data
Aqsa Reply
Kindly send me these notes.
Naheed
normal distribution
Akram
statistics
Akram
normal distribution
Shams
what is a regression, and what is it primarily used for
Denisha Reply
assume the sample populations do not have equal standard deviations and use the 0.05 significance level
Nokuthula Reply
what is the solution to this question?
Manbyen Reply
hi
Dewan
hello
Learn
hi please tell
Dewan

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Source:  OpenStax, Introductory statistics. OpenStax CNX. May 06, 2016 Download for free at http://legacy.cnx.org/content/col11562/1.18
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