Time series analysis in the social sciences : the fundamentals /

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Bibliographic Details
Author / Creator:Shin, Youseop, 1964- author.
Imprint:Oakland, California : University of California Press, [2017]
Description:1 online resource (xii, 232 pages)
Language:English
Subject:
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/11909888
Hidden Bibliographic Details
ISBN:9780520966383
0520966384
9780520293168
0520293169
9780520293175
0520293177
Notes:Includes bibliographical references and index.
In English.
Online resource; title from digital title page (viewed on February 03, 2017).
Summary:"This book focuses on fundamental elements of time-series analysis that social scientists need to understand to employ time-series analysis for their research and practice. Avoiding extraordinary mathematical materials, this book explains univariate time-series analysis step-by-step, from the preliminary visual analysis through the modeling of seasonality, trends, and residuals to the prediction and the evaluation of estimated models. Then, this book explains smoothing, multiple time-series analysis, and interrupted time-series analysis. At the end of each step, this book coherently provides an analysis of the monthly violent-crime rates as an example."--Provided by publisher.
Other form:Print version: Shin, Youseop, 1964- Time series analysis in the social sciences. Oakland, California : University of California Press, [2017] 9780520293168
Standard no.:10.1525/9780520966383
Description
Summary:

Times Series Analysis in the Social Sciences is a practical and highly readable introduction written exclusively for students and researchers whose mathematical background is limited to basic algebra. The book focuses on fundamental elements of time series analysis that social scientists need to understand so they can employ time series analysis for their research and practice. Through step-by-step explanations and using monthly violent crime rates as case studies, this book explains univariate time series from the preliminary visual analysis through the modeling of seasonality, trends, and residuals, to the evaluation and prediction of estimated models. The book also explains smoothing, multiple time series analysis, and interrupted time series analysis. With a wealth of practical advice and supplemental data sets wherein students can apply their knowledge, this flexible and friendly primer is suitable for all students in the social sciences.

Physical Description:1 online resource (xii, 232 pages)
Bibliography:Includes bibliographical references and index.
ISBN:9780520966383
0520966384
9780520293168
0520293169
9780520293175
0520293177