Introductory Statistics by Stephen Kokoska - Second Edition, 2015 from Macmillan Student Store
Student Site

Introductory Statistics

A Problem Solving ApproachSecond Edition ©2015New Edition Available Stephen Kokoska

Introductory Statistics: A Problem-Solving Approach is now supported by Sapling Intro Stats, a powerful online homework system in which every problem is an opportunity for a student to learn through meaningful hints, targeted feedback, and detailed solutions. Sapling Intro Stats provides stud...
Read more
Students - Buy or Rent

ISBN:9781319116842

ISBN:9781464157615

ISBN:9781319019044

ISBN:9781319019051

ISBN:9781319199296

ISBN:9781319199364

ISBN:9781319199340

ISBN:9781319199234

Introductory Statistics by Stephen Kokoska - Second Edition, 2015 from Macmillan Student Store

Stephen Kokoska blends solid mathematics with a distinctive problem-solving approach.

Introductory Statistics: A Problem-Solving Approach is now supported by Sapling Intro Stats, a powerful online homework system in which every problem is an opportunity for a student to learn through meaningful hints, targeted feedback, and detailed solutions. Sapling Intro Stats provides students with support to navigate their homework and ultimately understand statistical concepts and calculations. Read more at

www.macmillanlearning.com/saplingstats

Features

SAPLINGPLUS FOR STATISTICS

SaplingPlus is designed to teach by correcting students' misconceptions through targeted feedback, meaningful hints, and full solutions, helping teach students’ conceptual understanding and critical thinking in real-world contexts.

HINTS attached to select problems encourage critical thinking by providing
suggestions for completing the problem, without giving away the answer.

TARGETED FEEDBACK for select problems includes wrong answer specific feedback targeted to students’ misconceptions.

DETAILED FULLY-WORKED SOLUTIONS
reinforce concepts and provide an in-product study guide for every
problem in the Sapling Learning System.

LEARNINGCURVE’s adaptive quizzing encourages students to learn through practice. Through gamified elements, students are challenged to gain points by
submitting correct answers to meet or exceed an instructor-determined score. Faculty and students are then provided detailed analytics on their performance via their own personal study plan with pathways to additional learning tools and insights. This tool focuses
on getting students prepared for their upcoming class.

THE INTERACTIVE e-Book provides powerful study tools for
students, multimedia content, and easy customization for instructors. Students can search, highlight, and bookmark specific information, making it easier to study and access key content. Media assets such as data sets, glossary terms, select exercise answers, and
videos are linked within the e-book in SaplingPlus, allowing ease-of-use for students.

PRE-BUILT CHAPTER HOMEWORK ASSIGNMENTS are curated assignments containing questions directly from the book, with select questions containing error specific
feedback to guide students to concept mastery.

 

SAPLINGPLUS FOR STATISTICS

SaplingPlus provides online questions, including select assignment problems, for every chapter and on every important learning objective in the book. For select questions, students’ incorrect answers receive error-specific feedback based on common misconceptions about the topics.

HINTS attached to select problems encourage critical thinking by providing
suggestions for completing the problem, without giving away the answer.

TARGETED FEEDBACK for select problems includes wrong answer specific feedback targeted to students’ misconceptions.

DETAILED FULLY-WORKED SOLUTIONS reinforce concepts and provide an in-product study guide for every problem in the Sapling Learning System.

LEARNINGCURVE
Put “testing to learn” into action. Based on educational research, LearningCurve really works: Game-like quizzing motivates students and adapts to their needs based on their performance. It is the perfect tool to get students to engage before class and review after class. Additional reporting tools and metrics help instructors
get a handle on what their class knows and doesn’t know.

R CODE is provided to reproduce the complete analysis of all examples presented in the
main text of the book. This resource enables students to learn R further by example.
The code is available online at whitlockschluter3e.zoology.ubc.ca.

Labs Using R
A series of self-guided labs directs students through a week-by-week set of activities to reinforce key concepts and introduce the powerful free statistics package R. These labs are available online at whitlockschluter3e.zoology.ubc.ca.

DATA SETS
All data used in the book are real, and the data sets are available in electronic form
at whitlockschluter3e.zoology.ubc.ca and in SaplingPlus.

New to This Edition

LaunchPad
W.H. Freeman’s breakthrough online course space offers:

  • Pre-built Units for each chapter, curated by experienced educators, with media for each chapter organized and ready to assign or customize to suit your course.

  • All online resources for the text in one location, including an interactive e-book, LearningCurve adaptive quizzing, Try It Now exercises, StatTutor, video tech manuals, statistical applets, CrunchIt! statistical software, EESEE case studies, lecture videos, and optional sections.

  • Intuitive and useful analytics, with a Gradebook that lets you see how your class is doing individually and as a whole.

  • A streamlined interface that lets instructors build an entire course in minutes.


Revised Solution Trail Exercises
Kokoska’s unique Solution Trail framework in the text margin serves as a unique guide for approaching and solving the problems. To allow students to put this guidance to use, exercise sets now feature questions that ask students to create their own Solution Trails.


Approximately 40% New and Updated Exercises and Examples


New Concept Check Exercises
Each exercise set opens with true/false, fill-in-the-blank, and short-answer questions that help students solidify their understanding of essential statistical concepts.


New Chapter 0
This introductory chapter eases students into the course and Kokoska’s approach. It includes about a dozen exercises that teachers can assign for first day of class, helping students settle into the course more easily.


Revised Chapter Openers to include "Looking Forward/Looking Back"

"Looking Back" recaps key concepts learned in prior chapters. "Looking Forward" lists the key learning objectives covered in the chapter.

New "Last Step" Exercises Based on the Chapter Opening Question
The chapter-opening question is presented again as an exercise at the end of the chapter, to close the concept and application loop, as a last step.


Try It Now References
Most examples include a reference to a related exercise in the end-of-chapter set. With this, students can test their understanding of the examples’ concepts and techniques immediately.


More Statistical Technology Integration
In addition to Excel, Minitab, and TI-84C, the new edition incorporates output screens from Freeman’s CrunchIt!, as well as from JMP, in the narrative and examples (both software packages are available free of charge in LaunchPad).

Digital Options

LAUNCHPAD_FULL icon

LaunchPad

Get the e-book, do assignments, take quizzes, prepare for exams and more, to help you achieve success in class.

Learn About LaunchPad Schedule LaunchPad Demo Go to LaunchPad

SAPLING_HOMEWORK_STANDALONE icon

Sapling Learning

Do your homework online, with immediate feedback for optimum learning.

Learn About Sapling Learning Schedule Sapling Learning Demo

EPUB3_EBOOK icon

E-book

Read online (or offline) with all the highlighting and notetaking tools you need to be successful in this course.

Learn About E-book

Table of Contents

0. Why Study Statistics
The Science of Intuition
The Statistical Inference Procedure
Problem Solving
With a Little Help From Technology

1. An Introduction to Statistics and Statistical Inference
1.1 Statistics Today
1.2 Populations, Samples, Probability, and Statistics
1.3 Experiments and Random Samples

2. Tables and Graphs for Summarizing Data
2.1 Types of Data
2.2 Bar Charts and Pie Charts
2.3 Stem-and-Leaf Plots
2.4 Frequency Distributions and Histograms

3. Numerical Summary Measures
3.1 Measures of Central Tendency
3.2 Measures of Variability
3.3 The Empirical Rule and Measures of Relative Standing
3.4 Five-Number Summary and Box Plots

4 Probability
4.1 Experiments, Sample Spaces, and Events
4.2 An Introduction to Probability
4.3 Counting Techniques
4.4 Conditional Probability
4.5 Independence

5. Random Variables and Discrete Probability Distributions
5.1 Random Variables
5.2 Probability Distributions for Discrete Random Variables
5.3 Mean, Variance, and Standard Deviation for a Discrete Random Variable
5.4 The Binomial Distribution
5.5 Other Discrete Distributions

6. Continuous Probability Distributions
6.1 Probability Distributions for Continuous Random Variables
6.2 The Normal Distribution
6.3 Checking the Normality Assumption
6.4 The Exponential Distribution

7. Sampling Distributions
7.1 Statistics, Parameters, and Sampling Distributions
7.2 The Sampling Distribution of the Sample Mean and the Central
Limit Theorem
7.3 The Distribution of the Sample Proportion

8. Confidence Intervals Based on a Single Sample
8.1 Point Estimation
8.2 A Confidence Interval for a Population Mean when s Is Known
8.3 A Confidence Interval for a Population Mean when s Is Unknown
8.4 A Large-Sample Confidence Interval for a Population Proportion
8.5 A Confidence Interval for a Population Variance

9. Hypothesis Tests Based on a Single Sample
9.1 The Parts of a Hypothesis Test and Choosing the Alternative Hypothesis
9.2 Hypothesis Test Errors
9.3 Hypothesis Tests Concerning a Population Mean when s Is Known
9.4 p Values
9.5 Hypothesis Tests Concerning a Population Mean when s Is Unknown
9.6 Large-Sample Hypothesis Tests Concerning a Population Proportion
9.7 Hypothesis Tests Concerning a Population Variance or Standard Deviation

10. Confidence Intervals and Hypothesis Tests Based on Two Samples or Treatments
10.1 Comparing Two Population Means Using Independent Samples when Population Variances Are Known
10.2 Comparing Two Population Means Using Independent Samples from Normal Populations
10.3 Paired Data
10.4 Comparing Two Population Proportions Using Large Samples
10.5 Comparing Two Population Variances or Standard Deviations

11. The Analysis of Variance
11.1 One-Way ANOVA
11.2 Isolating Differences
11.3 Two-Way ANOVA

12. Correlation and Linear Regression
12.1 Simple Linear Regression
12.2 Hypothesis Tests and Correlation
12.3 Inferences Concerning the Mean Value and an Observed Value of Y for x 5 x*
12.4 Regression Diagnostics
12.5 Multiple Linear Regression

13. Categorical Data and Frequency Tables
13.1 Univariate Categorical Data, Goodness-of-Fit Tests
13.2 Bivariate Categorical Data, Tests for Homogeneity and Independence

14. Nonparametric Statistics
14.1 The Sign Test
14.2 The Signed-Rank Test
14.3 The Rank-Sum Test
14.4 The Kruskal–Wallis Test
14.5 The Runs Test
14.6 Spearman’s Rank Correlation

Notes and Data Sources
Tables Appendix
Answers to Odd-Numbered Exercises
Index

Optional Online Sections
Section 6.5 The Normal Approximation to the Binomial Distribution
Section 12.6 The Polynomial and Qualitative Predictor Models
Section 12.7 Model Selection Procedures

Stephen Kokoska

Steve Kokoska received his undergraduate degree from Boston College, and his M.S and Ph.D. from the University of New Hampshire. His initial research interests included the statistical analysis of cancer chemoprevention experiments. He has published a number of research papers in mathematics journals, including: Biometrics, Anticancer Research, and Computer Methods and Programs in Biomedicine. He has also presented results at national conferences, written several books, and been awarded grants from the National Science Foundation, the Center for Rural Pennsylvania, and the Ben Franklin Program.

Steve is a long-time consultant for the College Board and conducted workshops in Brazil, the Dominican Republic, and China. He was the AP Calculus Chief Reader for four years, and has been involved with calculus reform and the use of technology in the classroom. He has been teaching at Bloomsburg University for 25years and recently served as Director of the Honors Program.

Steve has been teaching introductory statistics classes throughout his academic career, and there is no doubt that this is his favorite course. This class (and text) provides students with basic, life-long, quantitative skills that they will use in almost any job and teaches them how to think and reason logically. Steve believes very strongly in data-driven decisions and conceptual understanding through problem solving.

Instructor Resources

Need instructor resources for your course?

Unlock Your Resources

Instructor Resources

Access Test Bank

You need to sign in as a verified instructor to access the Test Bank.

request locked icon

Test Bank for Introductory Statistics (Online Only)

Stephen Kokoska | Second Edition | ©2015 | ISBN:9781464157493

Learn more about our Test Banks.

Go To Test Bank

Download Resources

You need to sign in to unlock your resources.

request locked icon

Image PowerPoint Slides

Instructor Solutions Manual for Introductory Statistics (Online Only)

Stephen Kokoska | Second Edition | ©2015 | ISBN:9781464157516
request locked icon

Lecture PowerPoint Slides

request locked icon

Request Access to CrunchIt!

request locked icon

iClicker Questions