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Note: Supplemental materials are not guaranteed with Rental or Used book purchases.
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Praise for the First Edition
“...a well-written book on data analysis and data mining that provides an excellent foundation...”
—CHOICE
“This is a must-read book for learning practical statistics and data analysis...”
—Computing Reviews.com
A proven go-to guide for data analysis, Making Sense of Data I: A Practical Guide to Exploratory Data Analysis and Data Mining, Second Edition focuses on basic data analysis approaches that are necessary to make timely and accurate decisions in a diverse range of projects. Based on the authors’ practical experience in implementing data analysis and data mining, the new edition provides clear explanations that guide readers from almost every field of study.
PREFACE ix
1 INTRODUCTION 1
1.1 Overview 1
1.2 Sources of Data 2
1.3 Process for Making Sense of Data 3
1.4 Overview of Book 13
1.5 Summary 16
Further Reading 16
2 DESCRIBING DATA 17
2.1 Overview 17
2.2 Observations and Variables 18
2.3 Types of Variables 20
2.4 Central Tendency 22
2.5 Distribution of the Data 24
2.6 Confidence Intervals 36
2.7 Hypothesis Tests 40
Exercises 42
Further Reading 45
3 PREPARING DATA TABLES 47
3.1 Overview 47
3.2 Cleaning the Data 48
3.3 Removing Observations and Variables 49
3.4 Generating Consistent Scales Across Variables 49
3.5 New Frequency Distribution 51
3.6 Converting Text to Numbers 52
3.7 Converting Continuous Data to Categories 53
3.8 Combining Variables 54
3.9 Generating Groups 54
3.10 Preparing Unstructured Data 55
Exercises 57
Further Reading 57
4 UNDERSTANDING RELATIONSHIPS 59
4.1 Overview 59
4.2 Visualizing Relationships Between Variables 60
4.3 Calculating Metrics About Relationships 69
Exercises 81
Further Reading 82
5 IDENTIFYING AND UNDERSTANDING GROUPS 83
5.1 Overview 83
5.2 Clustering 88
5.3 Association Rules 111
5.4 Learning Decision Trees from Data 122
Exercises 137
Further Reading 140
6 BUILDING MODELS FROM DATA 141
6.1 Overview 141
6.2 Linear Regression 149
6.3 Logistic Regression 161
6.4 k-Nearest Neighbors 167
6.5 Classification and Regression Trees 172
6.6 Other Approaches 178
Exercises 179
Further Reading 182
APPENDIX A ANSWERS TO EXERCISES 185
APPENDIX B HANDS-ON TUTORIALS 191
B.1 Tutorial Overview 191
B.2 Access and Installation 191
B.3 Software Overview 192
B.4 Reading in Data 193
B.5 Preparation Tools 195
B.6 Tables and Graph Tools 199
B.7 Statistics Tools 202
B.8 Grouping Tools 204
B.9 Models Tools 207
B.10 Apply Model 211
B.11 Exercises 211
BIBLIOGRAPHY 227
INDEX 231
The New copy of this book will include any supplemental materials advertised. Please check the title of the book to determine if it should include any access cards, study guides, lab manuals, CDs, etc.
The Used, Rental and eBook copies of this book are not guaranteed to include any supplemental materials. Typically, only the book itself is included. This is true even if the title states it includes any access cards, study guides, lab manuals, CDs, etc.