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How to Make Sense of Statistics

Gorard, Stephen
Innbundet / 2021 / Engelsk

Produktdetaljer

ISBN
9781526413819
Publisert
2021-02-24
Utgiver
Vendor
SAGE Publications Ltd
Vekt
670 gr
Høyde
242 mm
Bredde
170 mm
Aldersnivå
U, 05
Språk
Product language
Engelsk
Format
Product format
Innbundet
Antall sider
320

Forfatter
Gorard, Stephen

Biographical note

Stephen Gorard is Professor of Education and Public Policy, and Director of the Evidence Centre for Education, at Durham University (https://www.dur.ac.uk/). He is a Fellow of the Academy of Social Sciences, member of the ESRC Commissioning Panel for the Research Methods Programme, the British Academy grants panel, and Lead Editor for BERA’s Review of Education. He is a member of the Cabinet Office Trials Advice Panel as part of the Prime Minister’s Implementation Unit. His work concerns the robust evaluation of education as a lifelong process, focused on issues of equity, especially regarding school intakes. He is author of around 30 books and over 1,000 other publications. He is currently funded by Nesta to evaluate their EdTech Testbed, and by the British Academy to look at the impact of schooling in India and Pakistan.  

How to Make Sense of Statistics

Gorard, Stephen
Innbundet / 2021 / Engelsk
Gorard, Stephen
Innbundet / 2021 / Engelsk
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This book takes beginner students hand-in-hand through a journey in the world of statistics without dumbing down the concepts, just making them very accessible. It teaches the basics (and beyond) by stimulating critical thinking.

- Luana Russo,

In a new textbook designed for students new to statistics and social data, Stephen Gorard focuses on non-inferential statistics as a basis to ensure students have basic statistical literacy.  Understanding why we have to learn statistics and seeing the links between the numbers and real life is a crucial starting point. Using engaging, friendly, approachable language this book will demystify numbers from the outset, explaining exactly how they can be used as tools to understand the relationships between variables.  This text assumes no previous mathematical or statistical knowledge, taking the reader through each basic technique with step-by-step advice, worked examples, and exercises. Using non-inferential techniques, students learn the foundations that underpin all statistical analysis and will learn from the ground up how to produce theoretically and empirically informed statistical results.
Les mer
In a new textbook designed for students new to statistics and social data, Gorard focuses on non-inferential statistics as a basis to provide readers with fundamental statistical literacy. Assuming no previous statistical knowledge, the author demystifies the subject in an engaging and approachable style.
Les mer
Part I: Introduction Chapter 1: Why we use numbers in research Chapter 2: What is a number?: Issues of measurement Part II: Basic analyses Chapter 3: Working with one variable Chapter 4: Working with tables of categorical variables Chapter 5: Examining differences between real numbers Chapter 6: Significance tests: how to conduct them and what they do not mean Chapter 7: Significance tests: why we should not report them Part III: Advanced issues for analysis Chapter 8: The role of judgement in analysis Chapter 9: Research designs Chapter 10: Sampling and populations Chapter 11: What is randomness? Chapter 12: Handling missing data: The importance of what we don’t know Chapter 13: Handling missing data: more complex issues Part IV: Modelling with data Chapter 14: Errors in measurements Chapter 15: Correlating two real numbers Chapter 16: Predicting measurements using simple linear regression Chapter 17: Predicting measurements using multiple linear regression Chapter 18: Assumptions and limitations in regression Chapter 19: Predicting outcomes using logistic regression Chapter 20: Data reduction techniques Part V: Conclusion Chapter 21: Presenting data for your audience
Les mer

Relaterte produkter

This book takes beginner students hand-in-hand through a journey in the world of statistics without dumbing down the concepts, just making them very accessible. It teaches the basics (and beyond) by stimulating critical thinking.

- Luana Russo,

In a new textbook designed for students new to statistics and social data, Stephen Gorard focuses on non-inferential statistics as a basis to ensure students have basic statistical literacy.  Understanding why we have to learn statistics and seeing the links between the numbers and real life is a crucial starting point. Using engaging, friendly, approachable language this book will demystify numbers from the outset, explaining exactly how they can be used as tools to understand the relationships between variables.  This text assumes no previous mathematical or statistical knowledge, taking the reader through each basic technique with step-by-step advice, worked examples, and exercises. Using non-inferential techniques, students learn the foundations that underpin all statistical analysis and will learn from the ground up how to produce theoretically and empirically informed statistical results.
Les mer
In a new textbook designed for students new to statistics and social data, Gorard focuses on non-inferential statistics as a basis to provide readers with fundamental statistical literacy. Assuming no previous statistical knowledge, the author demystifies the subject in an engaging and approachable style.
Les mer
Part I: Introduction Chapter 1: Why we use numbers in research Chapter 2: What is a number?: Issues of measurement Part II: Basic analyses Chapter 3: Working with one variable Chapter 4: Working with tables of categorical variables Chapter 5: Examining differences between real numbers Chapter 6: Significance tests: how to conduct them and what they do not mean Chapter 7: Significance tests: why we should not report them Part III: Advanced issues for analysis Chapter 8: The role of judgement in analysis Chapter 9: Research designs Chapter 10: Sampling and populations Chapter 11: What is randomness? Chapter 12: Handling missing data: The importance of what we don’t know Chapter 13: Handling missing data: more complex issues Part IV: Modelling with data Chapter 14: Errors in measurements Chapter 15: Correlating two real numbers Chapter 16: Predicting measurements using simple linear regression Chapter 17: Predicting measurements using multiple linear regression Chapter 18: Assumptions and limitations in regression Chapter 19: Predicting outcomes using logistic regression Chapter 20: Data reduction techniques Part V: Conclusion Chapter 21: Presenting data for your audience
Les mer

Produktdetaljer

ISBN
9781526413819
Publisert
2021-02-24
Utgiver
Vendor
SAGE Publications Ltd
Vekt
670 gr
Høyde
242 mm
Bredde
170 mm
Aldersnivå
U, 05
Språk
Product language
Engelsk
Format
Product format
Innbundet
Antall sider
320

Forfatter
Gorard, Stephen

Biographical note

Stephen Gorard is Professor of Education and Public Policy, and Director of the Evidence Centre for Education, at Durham University (https://www.dur.ac.uk/). He is a Fellow of the Academy of Social Sciences, member of the ESRC Commissioning Panel for the Research Methods Programme, the British Academy grants panel, and Lead Editor for BERA’s Review of Education. He is a member of the Cabinet Office Trials Advice Panel as part of the Prime Minister’s Implementation Unit. His work concerns the robust evaluation of education as a lifelong process, focused on issues of equity, especially regarding school intakes. He is author of around 30 books and over 1,000 other publications. He is currently funded by Nesta to evaluate their EdTech Testbed, and by the British Academy to look at the impact of schooling in India and Pakistan.  

Relaterte produkter