Time Series Analysis for the Social Sciences - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Time Series Analysis for the Social Sciences write by Janet M. Box-Steffensmeier. This book was released on 2014-12-22. Time Series Analysis for the Social Sciences available in PDF, EPUB and Kindle. Time series, or longitudinal, data are ubiquitous in the social sciences. Unfortunately, analysts often treat the time series properties of their data as a nuisance rather than a substantively meaningful dynamic process to be modeled and interpreted. Time Series Analysis for the Social Sciences provides accessible, up-to-date instruction and examples of the core methods in time series econometrics. Janet M. Box-Steffensmeier, John R. Freeman, Jon C. Pevehouse and Matthew P. Hitt cover a wide range of topics including ARIMA models, time series regression, unit-root diagnosis, vector autoregressive models, error-correction models, intervention models, fractional integration, ARCH models, structural breaks, and forecasting. This book is aimed at researchers and graduate students who have taken at least one course in multivariate regression. Examples are drawn from several areas of social science, including political behavior, elections, international conflict, criminology, and comparative political economy.
Applied Time Series Analysis for the Social Sciences
Applied Time Series Analysis for the Social Sciences - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Applied Time Series Analysis for the Social Sciences write by Richard McCleary. This book was released on 1980-07. Applied Time Series Analysis for the Social Sciences available in PDF, EPUB and Kindle. McCleary and Hay have made time series analysis techniques -- the Box-Jenkins or ARIMA methods -- accessible to the social scientist. Rejecting the dictum that time series analysis requires substantial mathematical sophistication, the authors take a clearly written, step-by-step approach. They describe the logic behind time series analysis, and its possible applications in impact assessment, causal modelling and forecasting, multivariate time series and parameter estimation.
Time-Series Analysis
Time-Series Analysis - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Time-Series Analysis write by John M. Gottman. This book was released on 2009-03-19. Time-Series Analysis available in PDF, EPUB and Kindle. Since the 1970s social scientists and scientists in a variety of fields - psychology, sociology, education, psychiatry, economics and engineering - have been interested in problems that require the statistical analysis of data over time and there has been in effect a conceptual revolution in ways of thinking about pattern and regularity. This book is a comprehensive introduction to all the major time-series techniques, both time-domain and frequency-domain. It includes work on linear models that simplify the solution of univariate and multivariate problems. The author begins with a non-mathematical overview: throughout, he provides easy-to-understand, fully worked examples drawn from real studies in psychology and sociology. Other, less comprehensive, books on time-series analysis require calculus: this presupposes only a standard introductory statistics course covering analysis of variance and regression. The chapters are short, designed to build concepts (and the reader's confidence) one step at a time. Many illustrations aid visual, intuitive understanding. Without compromising mathematical rigour, the author keeps in mind the reader who does no have an easy time with mathematics: the result is a readily accessible and practical text.
Time Series Analysis in the Social Sciences
Time Series Analysis in the Social Sciences - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Time Series Analysis in the Social Sciences write by Youseop Shin. This book was released on 2017-02-07. Time Series Analysis in the Social Sciences available in PDF, EPUB and Kindle. "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.
Introduction to Time Series Analysis
Introduction to Time Series Analysis - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Introduction to Time Series Analysis write by Mark Pickup. This book was released on 2014-10-15. Introduction to Time Series Analysis available in PDF, EPUB and Kindle. Introducing time series methods and their application in social science research, this practical guide to time series models is the first in the field written for a non-econometrics audience. Giving readers the tools they need to apply models to their own research, Introduction to Time Series Analysis, by Mark Pickup, demonstrates the use of—and the assumptions underlying—common models of time series data including finite distributed lag; autoregressive distributed lag; moving average; differenced data; and GARCH, ARMA, ARIMA, and error correction models. “This volume does an excellent job of introducing modern time series analysis to social scientists who are already familiar with basic statistics and the general linear model.” —William G. Jacoby, Michigan State University
