This First Edition of Statistics moves the curriculum in innovative ways while still looking relatively familiar. Statistics utilizes intuitive methods to introduce the fundamental idea of statistical inference. These intuitive methods are enabled through statistical software and are accessible at very early stages of a course. The text also includes the more traditional methods such as t-tests, chi-square tests, etc., but only after students have developed a strong intuitive understanding of inference through randomization methods.
The text is designed for use in a one-semester introductory statistics course. The focus throughout is on data analysis and the primary goal is to enable students to effectively collect data, analyze data, and interpret conclusions drawn from data. The text is driven by real data and real applications. Although the only prerequisite is a minimal working knowledge of algebra, students completing the course should be able to accurately interpret statistical results and to analyze straightforward data sets.
"Sinopsis" puede pertenecer a otra edición de este libro.
An accessible and practical introduction to clustering using a minimum of mathematics. This extensively revised edition contains detailed descriptions of the latest methods along with numerous examples and updated information on available software packages. Closing chapters provide suggestions which will be helpful in many situations when applying clustering or evaluating results.From the Back Cover:
Cluster Analysis: 5th Edition
Brian S. Everitt, Professor Emeritus, King's College, London, UK
Sabine Landau, Morven Leese and Daniel Stahl, Institute of Psychiatry, King's College London, UK
Cluster analysis comprises a range of methods for classifying multivariate data into subgroups. By organizing multivariate data into such subgroups, clustering can help reveal the characteristics of any structure or patterns present. These techniques have proven useful in a wide range of areas such as medicine, psychology, market research and bioinformatics.
This 5th edition of the highly successful Cluster Analysis includes coverage of the latest developments in the field and a new chapter dealing with finite mixture models for structured data.
Real life examples are used throughout to demonstrate the application of the theory, and figures are used extensively to illustrate graphical techniques. The book is comprehensive yet relatively non-mathematical, focusing on the practical aspects of cluster analysis.
· Presents a comprehensive guide to clustering techniques, with focus on the practical aspects of cluster analysis.
· Provides a thorough revision of the fourth edition, including new developments in clustering longitudinal data and examples from bioinformatics and gene studies
· Updates the chapter on mixture models to include recent developments and presents a new chapter on mixture modeling for structured data.
Practitioners and researchers working in cluster analysis and data analysis will benefit from this book.
"Sobre este título" puede pertenecer a otra edición de este libro.
Descripción Wiley, 1980. Estado de conservación: Good. 2nd. Former Library book. Shows some signs of wear, and may have some markings on the inside. Nº de ref. de la librería GRP82259255
Descripción Wiley, 1980. Estado de conservación: Good. 2nd. Shows some signs of wear, and may have some markings on the inside. Nº de ref. de la librería GRP37077644
Descripción John Wiley & Sons Inc, 1980. Hardcover. Estado de conservación: Used: Good. Nº de ref. de la librería SONG047026991X
Descripción Wiley. PAPERBACK. Estado de conservación: Good. 047026991X Good condition, binding and pages show signs of wear. Nº de ref. de la librería SKU1014577
Descripción Estado de conservación: Good. Book Condition: Good. Nº de ref. de la librería 97804702699164.0