Spectral Analysis of Time-Series Data by Rebecca M. Warner, Warner, David A. (Ed.) Kenny

Product Details

Synopsis

This book provides a thorough introduction to methods for detecting and describing cyclic patterns in time-series data. It is written both for researchers and students new to the area and for those who have already collected time-series data but wish to learn new ways of understanding and presenting them. Facilitating the interpretation of observations of behavior, physiology, mood, perceptual threshold, social indicator variables, and other responses, the book focuses on practical applications and requires much less mathematical background than most comparable texts. Using real data sets and currently available software (SPSS for Windows), the author employs extensive examples to clarify key concepts. Topics covered include research design issues, preliminary data screening, identification and description of cycles, summary of results across time series, and assessment of relations between time series. Also considered are theoretical questions, problems of interpretation, and potential sources of artifact.

Annotation

The book contains black-and-white illustrations.

Booknews

Provides an introduction to methods for detecting and describing cyclic patterns in time-series data, for students and researchers new to this area and for those who have already collected time-series data and wish to learn new ways of understanding and presenting them. Focuses on practical applications and requires less mathematical background than most comparable works. Topics covered include research design, preliminary data screening, identification and description of cycles, assessment of relations between time series, and problems of interpretation. For those involved in behavioral and social sciences. Annotation c. by Book News, Inc., Portland, Or.

Biography

Rebecca M. Warner, PhD, is Professor of Psychology at the University of New Hampshire. Her research interests include communication style, cardiovascular reactivity and modulation of physiological rhythms in social interactions, and coordination of talk patterns in conversation.