text stringlengths 0 62.7k |
|---|
Brennan Davis California Polytechnic State University DATA Hunter Glanz California Polytechnic State University SCIENCE FOR ALL Content Development: David Dietz, Thomas Atwater, Amit Verma, Ravi Indiver Content Management: Laura Briskman, Monique Bettencourt Content Production: Mahalakshmi Usha, Nupur Anand, Audra Wals... |
Please contact www.AskPearsonSupport.com with any queries on this content. Pearson puts care into the creation of our products. Our learning materials undergo content reviews to minimize bias and ensure the content is inclusive, accurate, and relevant. Please use this link to report instances of bias and inaccuracies: ... |
Cover images from Shutterstock, D.R.3D/Shutterstock, AAVAA / Shutterstock, and NasonovVasiliy/Shutterstock. |
Microsoft and/or its respective suppliers make no representations about the suitability of the information contained in the documents and related graphics published as part of the services for any purpose. All such documents and related graphics are provided “as is” without warranty of any kind. Microsoft and/or its re... |
The documents and related graphics contained herein could include technical inaccuracies or typographical errors. Changes are periodically added to the information herein. Microsoft and/or its respective suppliers may make improvements and/or changes in the product(s) and/or the program(s) described herein at any time.... |
Microsoft® and Windows® are registered trademarks of the Microsoft Corporation in the U.S.A. and other countries. This book is not sponsored or endorsed by or affiliated with the Microsoft Corporation. |
Copyright © 2026 by Pearson Education, Inc. or its affiliates. All Rights Reserved. This digital publication is protected by copyright, and permission should be obtained from the publisher prior to any prohibited reproduction, storage in a retrieval system, or transmission in any form or by any means, electronic, mecha... |
Acknowledgments of third-party content appear on the appropriate page within the text. |
PEARSON and ALWAYS LEARNING are exclusive trademarks in the U.S. and/or other countries owned by Pearson Education, Inc. or its affiliates. |
Unless otherwise indicated herein, any third-party trademarks that may appear in this work are the property of their respective owners and any references to third-party trademarks, logos or other trade dress are for demonstrative or descriptive purposes only. Such references are not intended to imply any sponsorship, e... |
Library of Congress Cataloging-in-Publication Data |
Data Science For All Library of Congress Cataloging in Publication Control Number: 2024044768 |
$PrintCode Rental Edition: ISBN 10: 0-13-832314-3 ISBN 13: 978-0-13-832314-1 |
Print Offer: ISBN 10: 0-13-531141-1 ISBN 13: 978-0-13-531141-7 DEDICATION |
To my beautiful wife, Anna, for her unwavering support and culinary delights; to my sons, Canyon, Levi, and Tobin, who were my pillars of encouragement; and to my son, Noe, and his wife, Dani, for their unwavering backing—this book is a testament to your love and support. —Brennan |
To my family, Maddie and Jake, for their unconditional support throughout all of this. To all of my friends and other family for always being there, no matter what. —Hunter ABOUT THE AUTHORS |
Brennan Davis is the Richard and Julie Hood Professor and director of graduate analytics programs at the Orfalea College of Business at California Polytechnic State University (Cal Poly, San Luis Obispo). He received a BS in mathemat- ics from the University of California, Los Angeles, an MBA from the Wharton School of... |
Hunter Glanz is a Professor of Statistics and Data Science at California Polytechnic State University (Cal Poly, San Luis Obispo). He received a BS in mathematics and a BS in statis- tics from Cal Poly, followed by an MA and PhD in statistics from Boston University. He maintains a passion for data sci- ence, machine le... |
iv CONTENTS |
About the Authors iv Preface x Acknowledgments xviii Reviewers xix Index of Activities xxi |
Chapter 1: What Is Data Science? 1 |
Section 1.1: Introduction to Data Science 3 |
Section 1.2: Data in Tables 8 |
Section 1.3: Data Preparation 16 |
Section 1.4: Data Analysis and Storytelling 20 |
Section 1.5: Data Science in Society and Industry 24 |
Chapter 1: Putting It Together 27 |
Chapter 1: Ethics in Practice: Some Risks in Data Science 28 |
Chapter 1: Key Terms 29 |
Chapter 1: Chapter Review Questions 30 |
Chapter 1: Explaining the Concepts 31 |
Chapter 1: Applying the Concepts 32 |
Chapter 2: Data Wrangling: Preprocessing 39 |
Section 2.1: What Is Data Wrangling? 41 |
Section 2.2: Cleaning Missing Data 44 |
Section 2.3: Cleaning Anomalous Values 51 |
Section 2.4: Transforming Quantitative Variables 55 |
Section 2.5: Transforming Categorical Variables 58 |
Section 2.6: Reshaping a Dataset 62 |
Section 2.7: Combining Datasets 64 |
Chapter 2: Putting It Together 67 |
Chapter 2: Ethics in Practice: Othering 68 |
Chapter 2: Key Terms 68 |
Chapter 2: Chapter Review Questions 68 |
Chapter 2: Explaining the Concepts 74 |
Chapter 2: Applying the Concepts 75 |
Chapter 2: Tech Center 78 |
vi Contents |
Chapter 3: Making Sense of Data through Visualization 88 |
Section 3.1: The Grammar of Graphics 91 |
Section 3.2: Visualizations with One Quantitative Variable 93 |
Section 3.3: Visualizations with One Categorical Variable 105 |
Section 3.4: Visualizations with Two Variables 108 |
Section 3.5: Visualizations with Three or More Variables 121 |
Section 3.6: The Dangers of Visual Misrepresentation 129 |
Section 3.7: Data Visualization Guidelines 135 |
Chapter 3: Putting It Together 140 |
Chapter 3: Ethics in Practice: The Perils of Using Color 141 |
Chapter 3: Key terms 143 |
Chapter 3: Chapter Review Questions 144 |
Chapter 3: Explaining the Concepts 155 |
Chapter 3: Applying the Concepts 156 |
Chapter 3: Tech Center 161 |
Chapter 4: Exploratory Data Analysis 174 |
Section 4.1: Central Tendency 177 |
Section 4.2: Variability 179 |
Section 4.3: Shape 183 |
Section 4.4: Resistant Central Tendency and Variability 186 |
Section 4.5: Data Associations 189 |
Section 4.6: Identifying Outliers 203 |
Chapter 4: Putting It Together 207 |
Chapter 4: Ethics in Practice: Simpson’s Paradox 207 |
Chapter 4: Key terms 209 |
Chapter 4: Chapter Review Questions 209 |
Chapter 4: Explaining the Concepts 211 |
Chapter 4: Applying the Concepts 212 |
Chapter 4: Tech Center 216 |
Chapter 5: Data Management 227 |
Section 5.1: Asking Questions of Data 229 |
Section 5.2: Selecting Variables 232 |
Section 5.3: Filtering and Ordering Observations 234 |
Section 5.4: Summarizing and Structuring Data 240 Contents vii |
Section 5.5: Merging Tables 242 |
Chapter 5: Putting It Together 246 |
Chapter 5: Ethics in Practice: Data Privacy Regulation 247 |
Chapter 5: Key Terms 247 |
End of preview. Expand in Data Studio
README.md exists but content is empty.
- Downloads last month
- 82