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Making sense of data I : a practical guide to exploratory data analysis and data mining / Glenn J. Myatt, Wayne P. Johnson.

By: Contributor(s): Material type: TextTextPublisher: Hoboken, New Jersey : John Wiley & Sons, Inc., [2014]Edition: Second editionDescription: 1 online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781118422014
  • 1118422015
  • 9781118422106
  • 1118422104
Uniform titles:
  • Making sense of data
Subject(s): Genre/Form: Additional physical formats: Print version:: Making sense of data I.DDC classification:
  • 006.3/12 23
LOC classification:
  • QA276
Online resources:
Contents:
Titlepage; Copyright; PREFACE; 1 INTRODUCTION; 1.1 Overview; 1.2 Sources of Data; 1.3 Process for Making Sense of Data; 1.4 Overview of Book; 1.5 Summary; Further Reading; 2 DESCRIBING DATA; 2.1 Overview; 2.2 Observations and Variables; 2.3 Types of Variables; 2.4 Central Tendency; 2.5 Distribution of the Data; 2.6 Confidence Intervals; 2.7 Hypothesis Tests; Exercises; Further Reading; 3 PREPARING DATA TABLES; 3.1 Overview; 3.2 Cleaning the Data; 3.3 Removing Observations and Variables; 3.4 Generating Consistent Scales Across Variables; 3.5 New Frequency Distribution
3.6 Converting Text to Numbers3.7 Converting Continuous Data to Categories; 3.8 Combining Variables; 3.9 Generating Groups; 3.10 Preparing Unstructured Data; Exercises; Further Reading; 4 UNDERSTANDING RELATIONSHIPS; 4.1 Overview; 4.2 Visualizing Relationships Between Variables; 4.3 Calculating Metrics About Relationships; Exercises; Further Reading; 5 IDENTIFYING AND UNDERSTANDING GROUPS; 5.1 Overview; 5.2 Clustering; 5.3 Association Rules; 5.4 Learning Decision Trees from Data; Exercises; Further Reading; 6 BUILDING MODELS FROM DATA; 6.1 Overview; 6.2 Linear Regression
6.3 Logistic Regression6.4 K-Nearest Neighbors; 6.5 Classification and Regression Trees; 6.6 Other Approaches; Exercises; Further Reading; APPENDIX A ANSWERS TO EXERCISES; APPENDIX B HANDS-ON TUTORIALS; B.1 Tutorial Overview; B.2 Access and Installation; B.3 Software Overview; B.4 Reading in Data; B.5 Preparation Tools; B.6 Tables and Graph Tools; B.7 Statistics Tools; B.8 Grouping Tools; B.9 Models Tools; B.10 Apply Model; B.11 Exercises; BIBLIOGRAPHY; INDEX; END USER LICENSE AGREEMENT
Summary: "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. In order to facilitate the needed steps when handling a data analysis or data mining project, a step-by-step approach aids professionals in carefully analyzing data and implementing results, leading to the development of smarter business decisions." -- Portion of summary from book.
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Revised editon of: Making sense of data. c2007.

Includes bibliographical references and index.

Print version record and CIP data provided by publisher.

"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. In order to facilitate the needed steps when handling a data analysis or data mining project, a step-by-step approach aids professionals in carefully analyzing data and implementing results, leading to the development of smarter business decisions." -- Portion of summary from book.

Titlepage; Copyright; PREFACE; 1 INTRODUCTION; 1.1 Overview; 1.2 Sources of Data; 1.3 Process for Making Sense of Data; 1.4 Overview of Book; 1.5 Summary; Further Reading; 2 DESCRIBING DATA; 2.1 Overview; 2.2 Observations and Variables; 2.3 Types of Variables; 2.4 Central Tendency; 2.5 Distribution of the Data; 2.6 Confidence Intervals; 2.7 Hypothesis Tests; Exercises; Further Reading; 3 PREPARING DATA TABLES; 3.1 Overview; 3.2 Cleaning the Data; 3.3 Removing Observations and Variables; 3.4 Generating Consistent Scales Across Variables; 3.5 New Frequency Distribution

3.6 Converting Text to Numbers3.7 Converting Continuous Data to Categories; 3.8 Combining Variables; 3.9 Generating Groups; 3.10 Preparing Unstructured Data; Exercises; Further Reading; 4 UNDERSTANDING RELATIONSHIPS; 4.1 Overview; 4.2 Visualizing Relationships Between Variables; 4.3 Calculating Metrics About Relationships; Exercises; Further Reading; 5 IDENTIFYING AND UNDERSTANDING GROUPS; 5.1 Overview; 5.2 Clustering; 5.3 Association Rules; 5.4 Learning Decision Trees from Data; Exercises; Further Reading; 6 BUILDING MODELS FROM DATA; 6.1 Overview; 6.2 Linear Regression

6.3 Logistic Regression6.4 K-Nearest Neighbors; 6.5 Classification and Regression Trees; 6.6 Other Approaches; Exercises; Further Reading; APPENDIX A ANSWERS TO EXERCISES; APPENDIX B HANDS-ON TUTORIALS; B.1 Tutorial Overview; B.2 Access and Installation; B.3 Software Overview; B.4 Reading in Data; B.5 Preparation Tools; B.6 Tables and Graph Tools; B.7 Statistics Tools; B.8 Grouping Tools; B.9 Models Tools; B.10 Apply Model; B.11 Exercises; BIBLIOGRAPHY; INDEX; END USER LICENSE AGREEMENT

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