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
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Mark Pickup is an associate professor in the Department of Political Science at Simon Fraser University. Mark is a specialist in political behavior and political methodology. Substantively, his research primarily falls into four areas: political identities and vote choice; the economy and democratic accountability; conditions of democratic responsiveness; and polls and electoral outcomes. His research focuses on political information, public opinion, political identities, and election campaigns within North American and European countries. His methodological interests concern the analysis of longitudinal data (time series, panel, network, etc.), with secondary interests in Bayesian analysis and survey/lab experiment design.
Approaching the topic from the perspective of the social scientist interested in hypothesis-testing, this volume is an introduction to time-series methods and their application in social science research.
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Approaching the topic from the perspective of the social scientist interested in hypothesis-testing, this volume is an introduction to time-series methods and their application in social science research.Über den AutorrnrnMark . Bestandsnummer des Verkäufers 880106480
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