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Quantitative Applications in the Social Sciences #70: Pooled Time Series Analysis

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Quantitative Applications in the Social Sciences #70: Pooled Time Series Analysis Cover

 

Synopses & Reviews

Synopsis:

Researchers have often been troubled with relevant data available from both temporal observations at regular intervals (time series) and from observations at single points of time (cross-sections). Pooled Time Series Analysis combines time series and cross-sectional data to provide the researcher with an efficient method of analysis and improved estimates of the population being studied. In addition, with more relevant data available this analysis technique allows the sample size to be increased, which ultimately yields a more effective study.

Product Details

ISBN:
9780803931602
Author:
Sayrs, Lois W.
Publisher:
Sage Publications, Inc
Location:
Newbury Park, Calif. :
Subject:
Research
Subject:
Time-series analysis
Subject:
Probability & Statistics - General
Subject:
Mathematics | Probability and Statistics
Edition Description:
Includes bibliographical references p. 77-78.
Series:
Quantitative Applications in the Social Sciences
Series Volume:
70
Publication Date:
19890531
Binding:
TRADE PAPER
Language:
English
Illustrations:
Yes
Pages:
80
Dimensions:
850x550

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  1. Quantitative Applications in the... New Trade Paper $15.50

Related Subjects

History and Social Science » Sociology » Reference and Methodology
History and Social Science » World History » General
Science and Mathematics » Mathematics » Probability and Statistics » General
Science and Mathematics » Mathematics » Probability and Statistics » Statistics
Science and Mathematics » Physics » General

Quantitative Applications in the Social Sciences #70: Pooled Time Series Analysis New Trade Paper
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Product details 80 pages Sage Publications - English 9780803931602 Reviews:
"Synopsis" by , Researchers have often been troubled with relevant data available from both temporal observations at regular intervals (time series) and from observations at single points of time (cross-sections). Pooled Time Series Analysis combines time series and cross-sectional data to provide the researcher with an efficient method of analysis and improved estimates of the population being studied. In addition, with more relevant data available this analysis technique allows the sample size to be increased, which ultimately yields a more effective study.
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