Introductory Statistics: A Problem-Solving Approach
Third Edition ©2020 Stephen Kokoska Formats: Achieve, E-book, Print
As low as C$77.99
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Authors
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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.
Table of Contents
Chapter 0 Why Study Statistics
Chapter 1 An Introduction to Statistics and Statistical Inference
Chapter 2 Tables and Graphs for Summarizing Data
Chapter 3 Numerical Summary Measures
Chapter 4 Probability
Chapter 5 Random Variables and Discrete Probability Distributions
Chapter 6 Continuous Probability Distributions
Chapter 7 Sampling Distributions
Chapter 8 Confidence Intervals Based on a Single Sample
Chapter 9 Hypothesis Tests Based on a Single Sample
Chapter 10 Confidence Intervals and Hypothesis Tests Based on Two Samples or Treatments
Chapter 11 The Analysis of Variance
Chapter 12 Correlation and Linear Regression
Chapter 13 Categorical Data and Frequency Tables
Chapter 14 Nonparametric Statistics
Optional Sections
(available online at macmillanlearning.com/introstats3e):
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
Product Updates
Focus on Statistical Inference. The main theme of this text is statistical inference and decision making through the interpretation of numerical results. The process of statistical inference is introduced in a variety of applications and statistical settings all using a similar, carefully delineated, four-step approach: Claim, Experiment, Likelihood, and Conclusion.
Step-by-Step Solutions. The solutions to selected examples are presented in logical, systematic steps. This approach helps guide the reader through the necessary calculations in order to find a solution and interpret results.
Solution Explanations. Each part in a solution is explained, or justified, so that the reader can easily follow each step in a solution.
A Closer Look. The details provided in these sections offer straightforward explanations of various definitions and concepts. The itemized specifics, including hints, tips, and reminders, make it easier for the reader to interpret, comprehend, and learn important statistical ideas.
How To Boxes. This feature provides clear steps for constructing basic graphs or performing essential calculations. The title in a How To box is color coded and easy to locate with each chapter.
Definition/Formula Boxes. Definitions and formulas are clearly marked and outlined with clean, crisp color-coded lines.
Data Sets. All data sets presented in the examples and exercises are available on the text’s website (www.macmillanlearning.com/introstats3e) in various formats. This makes it easy for students and instructors to use the most familiar and comfortable technology.
Grouped Exercises. There is a wide variety of interesting, engaging exercises on relevant topics, based on current data, at the end of each section. These problems provide plenty of opportunity for practice, review, and application of concepts. Exercises are grouped according to:
- Concept Check: True/False, Fill in the Blank, and Short Answer exercises designed to reinforce the basic concepts presented in the section.
- Practice: Basic, introductory problems to familiarize students with the relevant applications and solution methods.
- Applications: Realistic, appealing exercises to build confidence and promote routine understanding.
- Extended Applications: Applied problems that require extra creativity and thought.
- Challenge: Additional exercises and technology projects that allow students to
discover more advanced concepts and connections.
At the end of each chapter, Chapter Exercises help to test the students overall understanding of the chapter’s concepts and to practice for assessments. Answers to odd-numbered section and chapter exercises are given at the back of the book.
Chapter Summary. A table at the end of each chapter provides a short summary and page reference for each key concept, relevant notation, and formula.
Theory Symbols. In only a few places in the text, more advanced material is offset with blue, half-moon symbols. This material can be skipped by the typical reader, but provides more complete explanations of various topics.
In this completely redesigned third edition, Steve Kokoska combines his animated, interactive teaching style and friendly writing with contemporary real-world examples, modern pedagogical features, and the use of technology. The exposition presents precise mathematics with clear, often humorous, writing and a distinctive, organized solution process with reasons for every step. The following new features and enhancements build on the strong foundation set in previous editions.
Worked Example Videos. A video series focused on bringing Steve’s problem solving approach to life for students, via an audio/visual modality. Our community has ranked the five most difficult examples in every chapter, and these whiteboard-esque videos walk our learners through the application of the 4-step problem solving methodology used throughout the project.
Examples and Exercises. Over 30% of the Examples and Exercises have been updated with an even greater liberal arts character; a wide variety of interesting and contemporary topics are included. New applications include the chance of discovering a pearl in an oyster, air quality, trace minerals, and pickleball.
Chapter App. Each chapter begins with a unique, real-world problem, providing an interesting introduction to new concepts and an application to begin the discussion. Throughout the chapter, where relevant, Chapter App references provide questions and context that build up to the concluding Chapter App exercise.
Looking Back and Looking Forward. At the beginning of every chapter, the revised Looking Back feature includes reminders of specific concepts linked to earlier sections that will be used to develop new skills. The Looking Forward list includes the learning objectives for the chapter now linked to each section.
New subsections. Each section has been carefully broken down into smaller subsections to better facilitate comprehension and retrieval of information. Students now have a natural break to pause and reflect on what they have just learned, and to assess learning by trying specific exercises.
Common Error. This new marginal feature corrects common conceptual and computational errors in a just-in-time fashion.
Rapid Review. Icons in the text indicate key content where Rapid Review assessment can be found in your SaplingPlus course. Rapid Reviews provide a math refresher with short review quizzes or videos for help remembering basic math skills.
Focus on R software. Wherever possible, a technology solution using R is presented at the end of each text example. This allows students to focus on concepts and interpretation and gain a basic understanding of and familiarity with this widely-used open-source statistical program.
Check It Out. This marginal feature offers students a chance to stop and consider an important concept further in an informal way.
Authors
-
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.
Table of Contents
Chapter 0 Why Study Statistics
Chapter 1 An Introduction to Statistics and Statistical Inference
Chapter 2 Tables and Graphs for Summarizing Data
Chapter 3 Numerical Summary Measures
Chapter 4 Probability
Chapter 5 Random Variables and Discrete Probability Distributions
Chapter 6 Continuous Probability Distributions
Chapter 7 Sampling Distributions
Chapter 8 Confidence Intervals Based on a Single Sample
Chapter 9 Hypothesis Tests Based on a Single Sample
Chapter 10 Confidence Intervals and Hypothesis Tests Based on Two Samples or Treatments
Chapter 11 The Analysis of Variance
Chapter 12 Correlation and Linear Regression
Chapter 13 Categorical Data and Frequency Tables
Chapter 14 Nonparametric Statistics
Optional Sections
(available online at macmillanlearning.com/introstats3e):
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
Product Updates
Focus on Statistical Inference. The main theme of this text is statistical inference and decision making through the interpretation of numerical results. The process of statistical inference is introduced in a variety of applications and statistical settings all using a similar, carefully delineated, four-step approach: Claim, Experiment, Likelihood, and Conclusion.
Step-by-Step Solutions. The solutions to selected examples are presented in logical, systematic steps. This approach helps guide the reader through the necessary calculations in order to find a solution and interpret results.
Solution Explanations. Each part in a solution is explained, or justified, so that the reader can easily follow each step in a solution.
A Closer Look. The details provided in these sections offer straightforward explanations of various definitions and concepts. The itemized specifics, including hints, tips, and reminders, make it easier for the reader to interpret, comprehend, and learn important statistical ideas.
How To Boxes. This feature provides clear steps for constructing basic graphs or performing essential calculations. The title in a How To box is color coded and easy to locate with each chapter.
Definition/Formula Boxes. Definitions and formulas are clearly marked and outlined with clean, crisp color-coded lines.
Data Sets. All data sets presented in the examples and exercises are available on the text’s website (www.macmillanlearning.com/introstats3e) in various formats. This makes it easy for students and instructors to use the most familiar and comfortable technology.
Grouped Exercises. There is a wide variety of interesting, engaging exercises on relevant topics, based on current data, at the end of each section. These problems provide plenty of opportunity for practice, review, and application of concepts. Exercises are grouped according to:
- Concept Check: True/False, Fill in the Blank, and Short Answer exercises designed to reinforce the basic concepts presented in the section.
- Practice: Basic, introductory problems to familiarize students with the relevant applications and solution methods.
- Applications: Realistic, appealing exercises to build confidence and promote routine understanding.
- Extended Applications: Applied problems that require extra creativity and thought.
- Challenge: Additional exercises and technology projects that allow students to
discover more advanced concepts and connections.
At the end of each chapter, Chapter Exercises help to test the students overall understanding of the chapter’s concepts and to practice for assessments. Answers to odd-numbered section and chapter exercises are given at the back of the book.
Chapter Summary. A table at the end of each chapter provides a short summary and page reference for each key concept, relevant notation, and formula.
Theory Symbols. In only a few places in the text, more advanced material is offset with blue, half-moon symbols. This material can be skipped by the typical reader, but provides more complete explanations of various topics.
In this completely redesigned third edition, Steve Kokoska combines his animated, interactive teaching style and friendly writing with contemporary real-world examples, modern pedagogical features, and the use of technology. The exposition presents precise mathematics with clear, often humorous, writing and a distinctive, organized solution process with reasons for every step. The following new features and enhancements build on the strong foundation set in previous editions.
Worked Example Videos. A video series focused on bringing Steve’s problem solving approach to life for students, via an audio/visual modality. Our community has ranked the five most difficult examples in every chapter, and these whiteboard-esque videos walk our learners through the application of the 4-step problem solving methodology used throughout the project.
Examples and Exercises. Over 30% of the Examples and Exercises have been updated with an even greater liberal arts character; a wide variety of interesting and contemporary topics are included. New applications include the chance of discovering a pearl in an oyster, air quality, trace minerals, and pickleball.
Chapter App. Each chapter begins with a unique, real-world problem, providing an interesting introduction to new concepts and an application to begin the discussion. Throughout the chapter, where relevant, Chapter App references provide questions and context that build up to the concluding Chapter App exercise.
Looking Back and Looking Forward. At the beginning of every chapter, the revised Looking Back feature includes reminders of specific concepts linked to earlier sections that will be used to develop new skills. The Looking Forward list includes the learning objectives for the chapter now linked to each section.
New subsections. Each section has been carefully broken down into smaller subsections to better facilitate comprehension and retrieval of information. Students now have a natural break to pause and reflect on what they have just learned, and to assess learning by trying specific exercises.
Common Error. This new marginal feature corrects common conceptual and computational errors in a just-in-time fashion.
Rapid Review. Icons in the text indicate key content where Rapid Review assessment can be found in your SaplingPlus course. Rapid Reviews provide a math refresher with short review quizzes or videos for help remembering basic math skills.
Focus on R software. Wherever possible, a technology solution using R is presented at the end of each text example. This allows students to focus on concepts and interpretation and gain a basic understanding of and familiarity with this widely-used open-source statistical program.
Check It Out. This marginal feature offers students a chance to stop and consider an important concept further in an informal way.
A Problem Solving Approach
Now available with Macmillan’s Introductory Statistics helps students develop the fundamental lifelong skill of solving problems and interpreting solutions in real-world terms. One of our goals was to make this problem-solving approach accessible and easy to apply in many situations. We certainly want students to appreciate the beauty of statistics and connections to so many other disciplines. However, it is even more important for students to be able to apply problem-solving skills to a wide range of academic and career pursuits, including business, science and technology, and education.
Third Edition, presents long-term, universal skills for students taking a one- or two-semester introductory-level statistics course. Examples include guided, explanatory solutions that emphasize problem-solving techniques. Example solutions are presented in a numbered, step-by-step format. The generous collection and variety of exercises provide ample opportunity for practice and review in a variety of contexts. Concepts, examples, and exercises are presented from a practical, realistic perspective. Real and realistic data sets are current and relevant. The text uses mathematically correct notation and symbols and precise definitions to clearly illustrate statistical procedures and proper communication.
This text is designed to help students fully understand the steps in basic statistical arguments, emphasizing the importance of assumptions in order to follow valid arguments or identify inaccurate conclusions. Most importantly, students will understand the process of statistical inference. A four-step process (Claim, Experiment, Likelihood, Conclusion) is used throughout the text to present the smaller pieces of introductory statistics upon which the large, essential statistical inference puzzle is built.
Achieve for Introductory Statistics connects the problem-solving approach and real world examples in the book to rich digital resources that foster further understanding and application of statistics. Assets in Achieve support learning before, during, and after class for students, while providing instructors with class performance analytics in an easy-to-use interface.
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Stephen Kokoska | Third Edition | ©2020 | ISBN:9781319056063
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Our courses currently integrate with Canvas, Blackboard (Learn and Ultra), Brightspace, D2L, and Moodle. Click on the support documentation below to find out more details about the integration with each LMS.
Integrate Macmillan courses with Blackboard
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If you’re a verified instructor, you can request a free sample of our courseware, e-book, or print textbook to consider for use in your courses. Only registered and verified instructors can receive free print and digital samples, and they should not be sold to bookstores or book resellers. If you don't yet have an existing account with Macmillan Learning, it can take up to two business days to verify your status as an instructor. You can request a free sample from the right side of this product page by clicking on the "Request Instructor Sample" button or by contacting your rep. Learn more.
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Sometimes also referred to as a spiral-bound or binder-ready textbook, loose-leaf textbooks are available to purchase. This three-hole punched, unbound version of the book costs less than a hardcover or paperback book.
-
-
-
Achieve (full course) includes our complete e-book, as well as online quizzing tools, multimedia assets, and iClicker active classroom manager.
Most Achieve Essentials courses do not include our e-books and adaptive quizzing.
Visit our comparison table for details: https://www.macmillanlearning.com/college/us/digital/achieve/compare
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Achieve (full course) includes our complete e-book, as well as online quizzing tools, multimedia assets, and iClicker active classroom manager.
Achieve Read & Practice only includes our e-book and adaptive quizzing, and does not include instructor resources and assignable assessments. Read & Practice does integrate with LMS.
Visit our comparison table for details: https://www.macmillanlearning.com/college/us/digital/achieve/compare
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We can help! Contact your representative to discuss your specific needs for your course. If our off-the-shelf course materials don’t quite hit the mark, we also offer custom solutions made to fit your needs.
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Introductory Statistics: A Problem-Solving Approach
Now available with Macmillan’s Introductory Statistics helps students develop the fundamental lifelong skill of solving problems and interpreting solutions in real-world terms. One of our goals was to make this problem-solving approach accessible and easy to apply in many situations. We certainly want students to appreciate the beauty of statistics and connections to so many other disciplines. However, it is even more important for students to be able to apply problem-solving skills to a wide range of academic and career pursuits, including business, science and technology, and education.
Third Edition, presents long-term, universal skills for students taking a one- or two-semester introductory-level statistics course. Examples include guided, explanatory solutions that emphasize problem-solving techniques. Example solutions are presented in a numbered, step-by-step format. The generous collection and variety of exercises provide ample opportunity for practice and review in a variety of contexts. Concepts, examples, and exercises are presented from a practical, realistic perspective. Real and realistic data sets are current and relevant. The text uses mathematically correct notation and symbols and precise definitions to clearly illustrate statistical procedures and proper communication.
This text is designed to help students fully understand the steps in basic statistical arguments, emphasizing the importance of assumptions in order to follow valid arguments or identify inaccurate conclusions. Most importantly, students will understand the process of statistical inference. A four-step process (Claim, Experiment, Likelihood, Conclusion) is used throughout the text to present the smaller pieces of introductory statistics upon which the large, essential statistical inference puzzle is built.
Achieve for Introductory Statistics connects the problem-solving approach and real world examples in the book to rich digital resources that foster further understanding and application of statistics. Assets in Achieve support learning before, during, and after class for students, while providing instructors with class performance analytics in an easy-to-use interface.
These materials are owned by Macmillan Learning or its licensors and are protected by United States copyright law. They are being provided solely for evaluation purposes only by instructors who are considering adopting Macmillan Learning's textbooks or online products for use by students in their courses. These materials may not be copied, distributed, sold, shared, posted online, or used, in print or electronic format, except in the limited circumstances set forth in the Macmillan Learning Terms of Use and any other reproduction or distribution is illegal. These materials may not be made publicly available under any circumstances. All other rights reserved. © 2020 Macmillan Learning.
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