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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."
This book deals with the analysis of categorical data. Statistical models, especially log-linear models for contingency tables and logistic regression, are described and applied to real life data. Special emphasis is given to the use of graphical methods. The book is intended as a text for both undergraduate and graduate courses for statisticians, applied statisticians, social scientists, economists and epidemiologists. Many examples and exercises with solutions should help the reader to understand the material.
This book is intended as a textbook for a first course in applied
statistics for students of economics, public administration and
business administration. A limited knowledge of mathematics and -
in one single chapter - some knowledge of elementary matrix algebra
is required for understanding the text. Complicated mathematical
proofs are avoided and the explanations are based on intuition and
numerical examples. The aim of this book is to enable the student
to understand the reasoning underlying a statistical analysis and
to apply statistical methods to problems likely to be met within
the fields of economics, public administration and business
administration. The topics covered by the book are: - methods for
exploratory data analysis - probability theory and standard
statistical distributions - statistical inference theory - and
three main areas of application: regression analysis, survey
sampling and contingency tables. The treatment of exploratory data
analysis, regression analysis and the analysis of contingency
tables are based on the most recent theoretical developments in
these areas. Most of the examples have never been presented before
in English textbooks.
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