Interpreting quantitative data

How do quantitative methods help us to acquire knowledge of the real world? What are the 'do's' and 'don'ts' of effective quantitative research? This refreshing and accessible book provides students with a novel and useful resource for doing quantitative research. It offers students a guide on how to: interpret the complex reality of the social world; achieve effective measurement; understand the use of official statistics; use social surveys; understand probability and quantitative reasoning; interpret measurements; apply linear modelling; understand simulation and neural nets; and integrate quantitative and qualitative modelling in the research process. Jargon-free and written with the needs of students in mind, the book will be required reading for students interested in using quantitative research methods. Machine generated contents note: Introduction 1 1 Interpreting the Real and Describing the Complex: Why We Have to Measure 12 Positivism, realism and complexity 14 Naturalism - a soft foundationalist argument 17 There are no universals but, nevertheless, we can know 19 Models and measures: a first pass 21 Contingency and method - retroduction and retrodiction 25 Conclusion 27 2 The Nature of Measurement: What We Measure and How We Measure 29 Death to the variable 29 State space 32 Classification 34 Sensible and useful measuring 37 Conclusion 41 3 The State's Measurements: The Construction and Use of Official Statistics 44 The history of statistics as measures 45 Official and semi-official statistics 49 Social indicators 52 Tracing individuals 56 Secondary data analysis 57 Sources 57 Conclusion 58 4 Measuring the Complex World: The Character of Social Surveys 61 Knowledge production - the survey as process 63 Models from surveys - beyond the flowgraph? 66 Representative before random - sampling in the real world 72 Conclusion 77 5 Probability and Quantitative Reasoning 79 Objective probability versus the science of clues 80 Single case probabilities - back to the specific 84 Gold standard - or dross? 84 Understanding Head Start 88 Probabilistic reasoning in relation to non-experimental data 90 Randomness, probability, significance and investigation 92 Conclusion 93 6 Interpreting Measurements: Exploring, Describing and Classifying 95 Basic exploration and description 96 Making sets of categories - taxonomy as social exploration 99 Can classifying help us to sort out causal processes? 105 Conclusion 110 7 Linear Modelling: Clues as to Causes 112 Statistical models 113 Flowgraphs: partial correlation and path analysis 116 Working with latent variables - making things out of things that don't exist anyhow 117 Multi-level models 120 Statistical black boxes - Markov chains as an example 122 Loglinear techniques - exploring for interaction 123 Conclusion 128 8 Coping with Non-linearity and Emergence: Simulation and Neural Nets 130 Simulation - interpreting through virtual worlds 131 Micro-simulation - projecting on the basis of aggregation 133 Multi-agent models - interacting entities 135 Neural nets are not models but inductive empiricists 139 Models as icons, which are also tools 141 Using the tools 142 Conclusion 143 9 Qualitative Modelling: Issues of Meaning and Cause 145 From analytic induction through grounded theory to computer modelling - qualitative exploration of cause 147 Coding qualitative materials 150 Qualitative Comparative Analysis (QCA) - a Boolean approach 154 Iconic modelling 157 Integrative method 159 Conclusion 160 Conclusion 162 Down with: 162 Up with: 163 Action theories imply action164. 'Interpreting Quantitative Data' offers students a guide on how to interpret the complex reality of the social world, achieve effective measurement, understand the use of official statistics, use social surveys and apply linear modelling. Interpreting the Real and Describing the Complex: Why We Have to Measure -- The Nature of Measurement: What We Measure and How We Measure -- The State's Measurements: The Construction and Use of Official Statistics -- Measuring the Complex World: The Character of Social Surveys -- Probability and Quantitative Reasoning -- Interpreting Measurements: Exploring, Describing and Classifying -- Linear Modelling: Clues as to Causes -- Coping with Non-linearity and Emergence: Simulation and Neural Nets -- Qualitative Modelling: Issues of Meaning and Cause Student Textbook Examining Use Of Official Statistics, Social Surveys, Probability, Linear Modelling And Modelling. Interpreting The Real And Describing The Complex: Why We Have To Measure -- The Nature Of Measurement: What We Measure And How We Measure -- The State's Measurements: The Construction And Use Of Official Statistics -- Measuring The Complex World: The Character Of Social Surveys -- Probability And Quantitative Reasoning -- Interpreting Measurements: Exploring, Describing And Classifying -- Linear Modelling: Clues As To Causes -- Coping With Non-linearity And Emergence: Simulation And Neural Nets -- Qualitative Modelling: Issues Of Meaning And Cause. David Byrne. Includes Bibliographical References (p. [166]-170) And Index. COVER 1 Contents 6 Preface 10 Introduction 12 1 Interpreting the Real and Describing the Complex: Why We Have to Measure 23 2 The Nature of Measurement: What We Measure and How We Measure 40 3 The State’s Measurements: The Construction and Use of Official Statistics 55 4 Measuring the Complex World: The Character of Social Surveys 72 5 Probability and Quantitative Reasoning 90 6 Interpreting Measurements: Exploring, Describing and Classifying 106 7 Linear Modelling: Clues as to Causes 123 8 Coping with Non-linearity and Emergence: Simulation and Neural Nets 141 9 Qualitative Modelling: Issues of Meaning and Cause 156 Conclusion 173 Bibliography 177 Index 182 How do quantitative methods help us to acquire knowledge of the real world? What are the do's and don'ts of effective quantitative research? This refreshing and accessible textbook provides students with a novel and useful resource for doing quantitative research.