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008			201001s2020 xxu| s |||| 0|eng d
020			_a9781484261033
040			_dUNAV _bspa _cUEV
050			_bHF5548.4 _a.F69 2020 EB
082	0	4	_a005.7 _223
100	1		_aFoxwell, Harry J.
245	1	0	_aCreating Good Data : _h _bA Guide to Dataset Structure and Data Representation _cby Harry J. Foxwell
250			_a1st ed
260			_aBerkeley, CA _bApress _c2020
300			_a1 recurso en línea (XV, 105 p.)
336			_2rdacontent _aTexto (visual) _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
490	0		_aSpringer eBooks
505	0		_aChapter 1: The Need for Good Data -- Chapter 2: Basic Data Types and When to Use Them -- Chapter 3: Representing Quantitative Data -- Chapter 4: Planning Your Data Collection and Analysis -- Chapter 5: Good Datasets -- Chapter 6: Good Data Collection -- Chapter 7: Dataset Examples and Use Cases -- Chapter 8: Cleaning your Data -- Chapter 9: Good Data Anayltics -- Appendix A: Recommended Reading
520			_aCreate good data from the start, rather than fixing it after it is collected. By following the guidelines in this book, you will be able to conduct more effective analyses and produce timely presentations of research data. Data analysts are often presented with datasets for exploration and study that are poorly designed, leading to difficulties in interpretation and to delays in producing meaningful results. Much data analytics training focuses on how to clean and transform datasets before serious analyses can even be started. Inappropriate or confusing representations, unit of measurement choices, coding errors, missing values, outliers, etc., can be avoided by using good dataset design and by understanding how data types determine the kinds of analyses which can be performed. This book discusses the principles and best practices of dataset creation, and covers basic data types and their related appropriate statistics and visualizations. A key focus of the book is why certain data types are chosen for representing concepts and measurements, in contrast to the typical discussions of how to analyze a specific data type once it has been selected. You will: Be aware of the principles of creating and collecting data Know the basic data types and representations Select data types, anticipating analysis goals Understand dataset structures and practices for analyzing and sharing Be guided by examples and use cases (good and bad) Use cleaning tools and methods to create good data
538			_aForma de acceso: World Wide Web
650		7	_2embne _97256 _aBases de datos
710	2		_aSpringerLink
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=http://doi.org//10.1007/978-1-4842-6103-3 _zAcceso a este recurso digital (usuarios Universidad Europea de Valencia)
942			_2lcc _cLE
998			_db