Making sense of data I a practical guide to exploratory data analysis and data mining

"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...

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Bibliographic Details
Main Author: Myatt, Glenn J.
Other Authors: Johnson, Wayne P.
Format: eBook
Language:English
Published: Hoboken, New Jersey John Wiley & Sons, Inc. 2014
Edition:Second edition
Subjects:
Online Access:
Collection: O'Reilly - Collection details see MPG.ReNa
Table of Contents:
  • 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.
  • 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
  • Includes bibliographical references and index
  • 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