Making Sense of Data I
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Opis: Making Sense of Data I - Glenn Myatt, Wayne Johnson

With a focus on the needs of educators and students, "Making Sense of Data" presents the steps and issues that need to be considered in order to successfully complete a data analysis or data mining project. This "Second Edition" focuses on basic data analysis approaches that are necessary to complete a diverse range of projects. New examples have been added to illustrate the different approaches, and there is considerably more emphasis on hands-on software tutorials to provide real-world exercises. Via the related Web site, the book is accompanied by Traceis software, data sets, and tutorials; PowerPoint slides for classroom use; and other supplementary material to support educational classes. The authors provide clear explanations that guide readers to make timely and accurate decisions from data in almost every field of study. A step-by-step approach aids professionals in carefully analyzing data and implementing results, leading to the development of smarter business decisions. The topical coverage has been revised throughout to ensure only basic data analysis approaches are discussed, and new appendices have been added on the Traceis software as well as new tutorials using a variety of data sets with the software. Additional examples of data preparation, tables of graphs, statistics, grouping, and prediction have been included, and the topics of multiple linear regression and logistic regression have been added to provide a range of widely used and transparent approaches to performing classification and regression.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


Szczegóły: Making Sense of Data I - Glenn Myatt, Wayne Johnson

Tytuł: Making Sense of Data I
Autor: Glenn Myatt, Wayne Johnson
Producent: John Wiley
ISBN: 9781118407417
Rok produkcji: 2014
Ilość stron: 248
Oprawa: Miękka
Waga: 0.35 kg


Recenzje: Making Sense of Data I - Glenn Myatt, Wayne Johnson
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Making Sense of Data I

,

With a focus on the needs of educators and students, "Making Sense of Data" presents the steps and issues that need to be considered in order to successfully complete a data analysis or data mining project. This "Second Edition" focuses on basic data analysis approaches that are necessary to complete a diverse range of projects. New examples have been added to illustrate the different approaches, and there is considerably more emphasis on hands-on software tutorials to provide real-world exercises. Via the related Web site, the book is accompanied by Traceis software, data sets, and tutorials; PowerPoint slides for classroom use; and other supplementary material to support educational classes. The authors provide clear explanations that guide readers to make timely and accurate decisions from data in almost every field of study. A step-by-step approach aids professionals in carefully analyzing data and implementing results, leading to the development of smarter business decisions. The topical coverage has been revised throughout to ensure only basic data analysis approaches are discussed, and new appendices have been added on the Traceis software as well as new tutorials using a variety of data sets with the software. Additional examples of data preparation, tables of graphs, statistics, grouping, and prediction have been included, and the topics of multiple linear regression and logistic regression have been added to provide a range of widely used and transparent approaches to performing classification and regression.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

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Cena 276,00 PLN
Nasza cena 258,06 PLN
Oszczędzasz 6%
Wysyłka: Niedostępna
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Szczegóły: Making Sense of Data I - Glenn Myatt, Wayne Johnson

Tytuł: Making Sense of Data I
Autor: Glenn Myatt, Wayne Johnson
Producent: John Wiley
ISBN: 9781118407417
Rok produkcji: 2014
Ilość stron: 248
Oprawa: Miękka
Waga: 0.35 kg


Recenzje: Making Sense of Data I - Glenn Myatt, Wayne Johnson

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