Exploratory and descriptive statistics:
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Los Angeles ; London ; New Delhi ; Singapore ; Washington DC ; Melbourne
Sage
[2021]
|
| Schriftenreihe: | The Sage quantitative research kit
2nd volume |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | Enthält Literaturverzeichnis Seite 227-231 und Index |
| Beschreibung: | xv, 236 Seiten Illustrationen, Diagramme |
| ISBN: | 9781526424716 |
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Datensatz im Suchindex
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| adam_text | CONTENTS List of Figures, Tables and Boxes About the Authors 1 2 Introducing Descriptive and Exploratory Statistics ix xvii 1 What Is This Book About? What s in Each Chapter? New to Statistical Analysis? This Book Is for You! So, What Are Descriptive Statistics? What No Statistical Testing? Sounds Like Inferential Statistics Are More Important Types of Descriptive Statistics Categorical Data: Frequency Distributions Continuous or Interval-Level Data: Measures of Central Tendency Continuous or Interval-Level Data: Measures of Dispersion One Variable or Two? So, What Can I Do With Descriptive Statistics? Why Not Try Exploratory Data Analysis 2 2 4 4 9 9 10 10 13 13 15 16 20 Finding Data to Describe 23 Introduction Yours or Mine? What Is Primary Data? What Is Secondary Data? Know Thy Data What Do We Mean by Research Data? Administrative Data What s All This About Open Data ? Show Me the Data! A Little Exploration First Data, Data, Everywhere Accessing and Downloading Data Are You Sure About This Data? Should I Go Large? 24 24 24 26 27 27 28 30 32 32 33 34 35 36
vi EXPLORATORY AND DESCRIPTIVE STATISTICS 37 37 Downloading Data The General Social Survey The National Survey of Sexual Attitudes and Lifestyles 2010-2012 (Natsal-3) Got Data: Let s Look Inside! Problem Buster! Shit In, Shit Out: And Other Key Principles of Data Management Some Basic Cleaning Tips Looking Ahead 3 49 50 53 Measure Everything - Learn Something - Answer Nothing: An Exploration Intó’Variables and Types of Measurement Introduction Measurement as a Taken for Granted Measuring the Social World Controversial and Contested Measurements Units of Measurement: Variables Classification - Gender: Men and Women? Counting Gender: How Many Men and Women? Measurement: Different Experiences of Men and Women? Explaining: Different Experiences of Men and Women? Levels of Measurement Categorical Variables Nominal Ordinal Interval Variables Ordinal Scale Looking Ahead 4 42 48 49 55 . 56 57 60 64 64 65 66 70 71 72 74 74 74 74 74 75 77 I Am Not a Number, I Am a Categorical Variable 81 Introduction Percentages: A Story of Parts and Wholes Categorical Data and Percentages Working With Valid Percent and Percent: Working With Missing Data Presenting Percentages, Don t Forget then What s This Cumulative Percent Column All About? To Merge or Not to Merge Responses 82 85 87 95 97 98 98
CONTENTS 5 vii Writing Up Results: Producing Descriptive Summaries Show, Compare or Present Rounding Up or Down? What to Report With Missing Data? Strengths of Using the Percent Working With Contingency Tables How to Guides for IBM SPSS and MS Excel How to Guide for IBM SPSS Carrying Out Univariate Analysis IBM SPSS Outputs Two s Company: Carrying Out Bivariate Analysis Using IBM SPSS Bivariate Analysis: Including Percentages How to Guide for MS Excel Using MS Word to Make Frequency Tables Two s Company in MS Excel Looking Ahead 99 100 101 101 103 105 107 107 108 109 110 113 115 117 124 127 I Like Being Average, I Am an Interval Variable 131 Introduction Measures of Central Tendency and Dispersion Averages in Everyday Life: Feedback Scores The Importance of Averages: Exploring Income and Poverty Rich Man, Poor Man, Beggar Man, Thief: The Problem When Measuring Average Incomes What s Wrong With Being Average: Income Inequalities and the Problem With Outliers Measures of Dispersion: Adding More Context to the Data Singing Stats! Standard Deviation: Horrible Name, but Really Useful Home on the Range? Using the Range Rule for a Quick Standard Deviation Average UK Income: But Which Average? Bivariate Analysis U sing MCT When Averages Are Just Plain Silly I Am Above Average Actually! Writing Up the Results: The End Is Nigh How to Calculate MCT and MoD Using IBM SPSS How to Calculate MCT and MoD Using MS Excel Looking Ahead 132 132 133 134 136 137 141 143 143 144 145 147 148 149 149 ֊ 151 155 155
viii 6 7 ļ EXPLORATORY AND DESCRIPTIVE STATISTICS Visualising Our Data 159 Does a Picture Tell a Thousand Words? Does It Really Matter How I Present My Data? There s a Graph for That The One With the Slices The One With the Bars The One With the Lines The One With That Sounds Like Instagram The One With the Whiskers The One With All the Dots Spoilt for Choice! What Makes a Good Gfaph? Data Mapping Looking Ahead 160 160 164 164 169 174 176 182 185 189 189 191 197 The Story Waiting to Be Told 199 Introduction The Opposite Sex? The Gender Pay Gap Data Still Matters Measurement Still Matters Let s Talk About Sex Baby The Importance of Context When Exploring Data Beyond the Double Standard: Telling Stories of Sexual Difference Men Estimate - Women Count: A Gender Difference to Recollecting Trigger Warning! Statistics in the Media * The Transient Nature of the News Media Butter Is Good/Bad/Good/Bad/WTF for You! The Fine Line Between Mistakes and Misleading The Devil s in the Detail! Purveyors of Fake News! 200 201 202 203 205 205 207 209 210 210 213 213 216 217 217 Glossary References Index 221 227 233
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| adam_txt |
CONTENTS List of Figures, Tables and Boxes About the Authors 1 2 Introducing Descriptive and Exploratory Statistics ix xvii 1 What Is This Book About? What's in Each Chapter? New to Statistical Analysis? This Book Is for You! So, What Are Descriptive Statistics? What No Statistical Testing? Sounds Like Inferential Statistics Are More Important Types of Descriptive Statistics Categorical Data: Frequency Distributions Continuous or Interval-Level Data: Measures of Central Tendency Continuous or Interval-Level Data: Measures of Dispersion One Variable or Two? So, What Can I Do With Descriptive Statistics? Why Not Try Exploratory Data Analysis 2 2 4 4 9 9 10 10 13 13 15 16 20 Finding Data to Describe 23 Introduction Yours or Mine? What Is Primary Data? What Is Secondary Data? Know Thy Data What Do We Mean by Research Data? Administrative Data What's All This About Open Data'? Show Me the Data! A Little Exploration First Data, Data, Everywhere Accessing and Downloading Data Are You Sure About This Data? Should I Go Large? 24 24 24 26 27 27 28 30 32 32 33 34 35 36
vi EXPLORATORY AND DESCRIPTIVE STATISTICS 37 37 Downloading Data The General Social Survey The National Survey of Sexual Attitudes and Lifestyles 2010-2012 (Natsal-3) Got Data: Let's Look Inside! Problem Buster! Shit In, Shit Out: And Other Key Principles of Data Management Some Basic Cleaning Tips Looking Ahead 3 49 50 53 Measure Everything - Learn Something - Answer Nothing: An Exploration Intó’Variables and Types of Measurement Introduction Measurement as a Taken for Granted Measuring the Social World Controversial and Contested Measurements Units of Measurement: Variables Classification - Gender: Men and Women? Counting Gender: How Many Men and Women? Measurement: Different Experiences of Men and Women? Explaining: Different Experiences of Men and Women? Levels of Measurement Categorical Variables Nominal Ordinal Interval Variables Ordinal Scale Looking Ahead 4 42 48 49 55 . 56 57 60 64 64 65 66 70 71 72 74 74 74 74 74 75 77 I Am Not a Number, I Am a Categorical Variable 81 Introduction Percentages: A Story of Parts and Wholes Categorical Data and Percentages Working With Valid Percent and Percent: Working With Missing Data Presenting Percentages, Don't Forget then What's This Cumulative Percent Column All About? To Merge or Not to Merge Responses 82 85 87 95 97 98 98
CONTENTS 5 vii Writing Up Results: Producing Descriptive Summaries Show, Compare or Present Rounding Up or Down? What to Report With Missing Data? Strengths of Using the Percent Working With Contingency Tables How to Guides for IBM SPSS and MS Excel How to Guide for IBM SPSS Carrying Out Univariate Analysis IBM SPSS Outputs Two's Company: Carrying Out Bivariate Analysis Using IBM SPSS Bivariate Analysis: Including Percentages How to Guide for MS Excel Using MS Word to Make Frequency Tables Two's Company in MS Excel Looking Ahead 99 100 101 101 103 105 107 107 108 109 110 113 115 117 124 127 I Like Being Average, I Am an Interval Variable 131 Introduction Measures of Central Tendency and Dispersion Averages in Everyday Life: Feedback Scores The Importance of Averages: Exploring Income and Poverty Rich Man, Poor Man, Beggar Man, Thief: The Problem When Measuring Average Incomes What's Wrong With Being Average: Income Inequalities and the Problem With Outliers Measures of Dispersion: Adding More Context to the Data Singing Stats! Standard Deviation: Horrible Name, but Really Useful Home on the Range? Using the Range Rule for a 'Quick' Standard Deviation Average UK Income: But Which Average? Bivariate Analysis U sing MCT When Averages Are Just Plain Silly 'I Am Above Average Actually!' Writing Up the Results: The End Is Nigh 'How to'Calculate MCT and MoD Using IBM SPSS 'How to' Calculate MCT and MoD Using MS Excel Looking Ahead 132 132 133 134 136 137 141 143 143 144 145 147 148 149 149 ֊ 151 155 155
viii 6 7 ļ EXPLORATORY AND DESCRIPTIVE STATISTICS Visualising Our Data 159 Does a Picture Tell a Thousand Words? Does It Really Matter How I Present My Data? There's a Graph for That The One With the Slices The One With the Bars The One With the Lines The One With That Sounds Like Instagram The One With the Whiskers The One With All the Dots Spoilt for Choice! What Makes a Good Gfaph? Data Mapping Looking Ahead 160 160 164 164 169 174 176 182 185 189 189 191 197 The Story Waiting to Be Told 199 Introduction The Opposite Sex? The Gender Pay Gap Data Still Matters Measurement Still Matters 'Let's Talk About Sex Baby' The Importance of Context When Exploring Data Beyond the Double Standard: Telling Stories of Sexual Difference Men Estimate - Women Count: A Gender Difference to Recollecting Trigger Warning! Statistics in the Media * The Transient Nature of the News Media Butter Is Good/Bad/Good/Bad/WTF for You! The Fine Line Between Mistakes and Misleading The Devil's in the Detail! Purveyors of Fake News! 200 201 202 203 205 205 207 209 210 210 213 213 216 217 217 Glossary References Index 221 227 233 |
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| illustrated | Illustrated |
| index_date | 2024-07-03T18:39:05Z |
| indexdate | 2024-07-10T09:16:04Z |
| institution | BVB |
| isbn | 9781526424716 |
| language | English |
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| spelling | Jones, Julie Scott 1966- Verfasser (DE-588)141025492 aut Exploratory and descriptive statistics Julie Scott Jones, John Goldring Los Angeles ; London ; New Delhi ; Singapore ; Washington DC ; Melbourne Sage [2021] xv, 236 Seiten Illustrationen, Diagramme txt rdacontent n rdamedia nc rdacarrier The Sage quantitative research kit 2nd volume Enthält Literaturverzeichnis Seite 227-231 und Index Explorative Datenanalyse (DE-588)4128896-8 gnd rswk-swf Deskriptive Statistik (DE-588)4070313-7 gnd rswk-swf Deskriptive Statistik (DE-588)4070313-7 s Explorative Datenanalyse (DE-588)4128896-8 s DE-604 Goldring, John Verfasser (DE-588)1246325187 aut The Sage quantitative research kit 2nd volume (DE-604)BV047607953 2 Digitalisierung UB Regensburg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=032993325&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
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| title | Exploratory and descriptive statistics |
| title_auth | Exploratory and descriptive statistics |
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| title_full | Exploratory and descriptive statistics Julie Scott Jones, John Goldring |
| title_fullStr | Exploratory and descriptive statistics Julie Scott Jones, John Goldring |
| title_full_unstemmed | Exploratory and descriptive statistics Julie Scott Jones, John Goldring |
| title_short | Exploratory and descriptive statistics |
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