## Statistical analysis of categorical data

Material type: TextLanguage: English Publisher: London Springer Velrag 2020Edition: 3rd edDescription: xi,531 p. HB 24x16 cmISBN: 3540576967; 9783540576969Subject(s): Statistical Models | Statistical Inference | Multi dimension Contingency Tables | Latent Structural Analysis | The Logical ModelDDC classification: 519.535 Summary: The aim of this book is to give an up to date account of the most commonly uses statisti cal models for categorical data. The emphasis is on the connection between theory and applications to real data sets. The book only covers models for categorical data. Various models for mixed continuous and categorical data are thus excluded. The book is written as a textbook, although many methods and results are quite recent. This should imply, that the book can be used for a graduate course in categorical data analysis. With this aim in mind chapters 3 to 12 are concluded with a set of exer cises. In many cases, the data sets are those data sets, which were not included in the examples of the book, although they at one point in time were regarded as potential can didates for an example. A certain amount of general knowledge of statistical theory is necessary to fully benefit from the book. A summary of the basic statistical concepts deemed necessary pre requisites is given in chapter 2. The mathematical level is only moderately high, but the account in chapter 3 of basic properties of exponential families and the parametric multinomial distribution is made as mathematical precise as possible without going into mathematical details and leaving out most proofs.Item type | Current location | Collection | Call number | Status | Date due | Barcode | Item holds |
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Book | St Aloysius College (Autonomous) | Statistics | 519.535 ANDS (Browse shelf) | Available | 075635 |

The aim of this book is to give an up to date account of the most commonly uses statisti cal models for categorical data. The emphasis is on the connection between theory and applications to real data sets. The book only covers models for categorical data. Various models for mixed continuous and categorical data are thus excluded. The book is written as a textbook, although many methods and results are quite recent. This should imply, that the book can be used for a graduate course in categorical data analysis. With this aim in mind chapters 3 to 12 are concluded with a set of exer cises. In many cases, the data sets are those data sets, which were not included in the examples of the book, although they at one point in time were regarded as potential can didates for an example. A certain amount of general knowledge of statistical theory is necessary to fully benefit from the book. A summary of the basic statistical concepts deemed necessary pre requisites is given in chapter 2. The mathematical level is only moderately high, but the account in chapter 3 of basic properties of exponential families and the parametric multinomial distribution is made as mathematical precise as possible without going into mathematical details and leaving out most proofs.

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