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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

what is statistics
ADAM Reply
can anyone explain it better for me
ADAM
frequency distribution
Wasim Reply
noun STATISTICS a mathematical function showing the number of instances in which a variable takes each of its possible values.
Robin
ok
ADAM
Common language-- taking a bunch of information and seeing if it is related or not to other info
Mandy
Does standard deviation have measuring unit?
Mohamed
yes, the measuring unit of the data you are looking at, for example centimetres for height.
Emma
thanks
Mohamed
is that easy to plot a graph between three axis?
Mohamed
yes we can but we do not have that much effective tools. If the graph is normal or less complicated then it is plotted effectively otherwise it will give you nightmare.
umair
whats the difference between discrete and contineous data
umar
Discrete variables are variables that can assume finite number of values. Continuous variables are variables that can assume infinite number of values
Mike
i will give you an example: {0,4,84} it contains discrete or limited values like it can also contain boolean values{true,false} or {0,1} and continuous are like {1,2,3,4,5......} , {0,0.1,0.2,0.3,0.4...........}
umair
a no. of values which are countable are called discrete variables on the other hand, a no. of values which are not countable are called continuous variables
Aliya
Yup, I would like to support Mr.Umair's argument by saying that it can only apply if we have a 3-D graph,otherwise a plane graph will not apply at all
festus
Aliya and Mike thnks to both of you ❤❤
umar
what's variance
Sulaiman Reply
what's case control study?
Shakilla
hi
Noman
?
Sulaiman
what is covariance
Florence Reply
In probability theory and statistics, covariance is a measure of the joint variability of two random variables.[1] If the greater values of one variable mainly correspond with the greater values of the other variable, and the same holds for the lesser values, (i.e., the variables tend to show simila
Robin
Economics department, faculty of social sciences, NOUN. You are required to calculate: the covariance and State whether the covariance is positive or negative. (11½ marks) Observation E D 1 15 17.24 2 16 15.00 3 8 14.91 4 6 4.50 5 15 18.00 6 12 6.29 7 12 19.23 8 18 18.69 9 12 7.21 10 20 4
Florence
In probability theory and statistics, covariance is a measure of the joint variability of two random variables.
Robin
what is the purpose of statistics and why it is important that statistics to be a solo and one complete field?
Edu-info Reply
to organize,analyze and interpret information in order to make decision
Berema
what is noun?
Katama Reply
so simple. the name of any person,place or thing.
Edu-info
Using the Chi-square test, two coins were flipped a hundred times. What will be the chances of getting a head and getting a tale? Given observed values is 62 heads and 38 tails. Expected value is 50 heads, 50 tails. Is the difference due to chance or a significant error? a. Draw your hypothesis
DokBads Reply
how can I win
Jagogo Reply
what is difference between the blocking and confounding
Rukhsana Reply
how do you get 2/50 ?
CL Reply
can you explained it for me
korankye
an easier definition of inferential statistics
Kenedy Reply
Inferential statistics makes inferences and predictions about a population based on a sample of data taken from the population in question.
Rukhsana
Inferential statistics helps you to extract insights from a random sample data which then helps you to use specific predictive Modeling/machine learning technic to predict or forecast.
Manish
what is stemplot? can anyone explain?
Javokhirbek
what is statistics
ernest Reply
what is collection of data
ernest
no collection data was provided just the mean =14
Leticia
sd=14 describe the position of score to the mean how many points below or above z=1.00 z=1.50
Leticia
I have this sample score 14 18 12 22 14 22 21 20 13 26 13 26 16 21 they want me to.compute the z- score of x= 15 ×=40 and x=9?
Leticia
how do you understand that it is the mean?
Kenedy
fact and figure
hira
factors to consider when using secondary data
Edmond Reply
define binomial distribution
Samuel Reply
the distribution in which the outcome is of dichotomous
bimal
can you tell me Standar division is =14 what is the position of the score relative to the mean how many point above/below the mean?
Leticia
What do you call a measure of central tendency (i.e., average) appropriate for data measured on the continuous scale
DokBads Reply
arithmetic mean
bimal

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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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