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nach der Bestellung gedruckt Neuware - Printed after ordering - Researchers in the social sciences are faced with complex data sets in which they have relatively small samples and many variables (high dimensional data). Unlike the various technical guides currently on the market, this book provides and overview of a variety of models alongside clear examples of hands-on application. N° de ref. del artículo 9781032209470
Researchers in the social sciences are faced with complex data sets in which they have relatively small samples and many variables (high dimensional data). Unlike the various technical guides currently on the market, this book provides and overview of a variety of models alongside clear examples of hands-on application.
Acerca del autor:
Holmes Finch is the George and Frances Ball Distinguished Professor of Educational Psychology at BSU, and a professor of statistics and psychometrics. His research interests include structural equation modeling, item response theory, educational and psychological measurement, multilevel modeling, machine learning, and robust multivariate inference. In addition to conducting research in the field of statistics, he also regularly collaborates with colleagues in fields such as educational psychology, neuropsychology, and exercise physiology.
Título: Applied Regularization Methods for the ...
Editorial: Chapman And Hall/CRC
Año de publicación: 2024
Encuadernación: Taschenbuch
Condición: Neu