Assuming no previous knowledge, this book provides comprehensive coverage for a first course in research & statistical methods in computing, or it can be used as ""on the job"" self-training for professionals. It shows how to apply these methods to the current problems faced in a variety of fields, but with special emphasis on computer science and information systems. A research model applicable to applied research is proposed and discussed throughout the text. This model accommodates scientific methods of research, including empirical, quantitative, qualitative, case study, and mixed methods. Using a non-threatening approach to the subject, the text avoids excessive mathematics and abstract theory. It includes numerous exercises and examples that help students understand the relevance of research methodology applications, a DVD with statistical tables, data files, etc. Numerous instructors' resources are available upon adoption. This book has the following selected topics: Introduction to statistics; descriptive statistics; data mining; probability; estimation; hypothesis testing; chi-square tests; linear regression; variance; random-number generation; guide to research; model construction; statistical software; axiomatic research; simulation and clustering methods; simulations; statistical tables.

Cluster analysis is used in data mining and is a common technique for statistical data analysis used in many fields of study, such as the medical & life sciences, behavioral & social sciences, engineering, and in computer science. Designed for training industry professionals or for a course on clustering and classification, it can also be used as a companion text for applied statistics. No previous experience in clustering or data mining is assumed. Informal algorithms for clustering data and interpreting results are emphasized. In order to evaluate the results of clustering and to explore data, graphical methods and data structures are used for representing data. Throughout the text, examples and references are provided, in order to enable the material to be comprehensible for a diverse audience. A companion disc includes numerous appendices with programs, data, charts, solutions, etc. eBook Customers: Companion files are available for downloading with order number/proof of purchase by writing to the publisher at [email protected]. Features: Places emphasis on illustrating the underlying logic in making decisions during the cluster analysis Discusses the related applications of statistic, e.g., Ward's method (ANOVA), JAN (regression analysis & correlational analysis), cluster validation (hypothesis testing, goodness-of-fit, Monte Carlo simulation, etc.) Contains separate chapters on JAN and the clustering of categorical data Includes a companion disc with solutions to exercises, programs, data sets, charts, etc.