Topological Data Analysis: Research Methods: Bloomsbury Research Methods
Autor Dr Simon Rudkinen Limba Engleză Hardback – 9 feb 2027
This emerging data science tool is central to model evaluation, research development and the visualisation of multivariate datasets. Despite the many benefits of data visualisation, empirical work often undervalues the data upon which statistical inferences are later drawn. Where there are visualisations, the ability to truly see what is happening within our data is constrained by the plots employed. TDABM offers a means to overcome these limitations to realise the benefits of visualisation.
Taking an intuitive approach that shows how the necessary code can be constructed in R, examples throughout the book enable readers to build their analysis to suit whatever projects they are currently working on. This complete introduction to TDABM shows how it is informing and underpinning research in the social sciences and gives readers the confidence to apply it to their own data.
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Specificații
ISBN-13: 9781350564381
ISBN-10: 1350564389
Pagini: 256
Dimensiuni: 156 x 234 x 25 mm
Greutate: 0.45 kg
Editura: Bloomsbury Publishing
Colecția Bloomsbury Academic
Seria Bloomsbury Research Methods
Locul publicării:London, United Kingdom
ISBN-10: 1350564389
Pagini: 256
Dimensiuni: 156 x 234 x 25 mm
Greutate: 0.45 kg
Editura: Bloomsbury Publishing
Colecția Bloomsbury Academic
Seria Bloomsbury Research Methods
Locul publicării:London, United Kingdom
Cuprins
Series Editor Foreword
Preface to the Second Edition
Acknowledgements
1. Data and Data Visualisation
2. Topological Data Analysis
3. Topological Data Analysis Ball Mapper Algorithm
4. Evaluating Statistical Models
5. Extensions
6. Implementation in R
Glossary
Bibliography
Index
Preface to the Second Edition
Acknowledgements
1. Data and Data Visualisation
2. Topological Data Analysis
3. Topological Data Analysis Ball Mapper Algorithm
4. Evaluating Statistical Models
5. Extensions
6. Implementation in R
Glossary
Bibliography
Index