Description
Discover the transformative book, *Quantitative Analysis for Historical Social Science*, a groundbreaking text that bridges the gap between qualitative and quantitative analysis in historical research. This vital resource is authored by esteemed scholars Gregory Wawro and Ira Katznelson, who present innovative methodologies to enhance your understanding of social science history. This trade paperback, published in 2022 by Princeton University Press, is a must-have for historians, social scientists, and researchers alike, seeking to enrich their analytical toolbox with robust quantitative methods that capture the nuances of historical data.
By addressing key criticisms of traditional statistical methods, Wawro and Katznelson introduce advanced techniques tailored to handle temporality, periodicity, specificity, and context—attributes essential for sound historical analysis. Unlock powerful insights as the authors exemplify these methods through replicative research that highlights structural breaks and temporal evolution. They also provide valuable practices for examining path dependence using time-series data, ultimately enhancing causal inference in historical studies.
Whether you are exploring historical patterns or conducting empirical investigations, *Quantitative Analysis for Historical Social Science* equips you with the knowledge needed to elevate your research approach. Shipping for this item is FREE, however, please allow 6 weeks for shipping. Kindly note, once you place the order, we are unable to cancel it. Perfect for academics and a valuable addition to your personal library, order your brand new copy today and delve into the innovative world of historical social science analysis.
Shipping for this item is FREE, however please allow 6 weeks for shipping, please note once you place the order we are not able to cancel it.
Condition: BRAND NEW
ISBN: 9780691155050
Format: Trade paperback (US)
Year: 2022
Publisher: Princeton University Press
Description:
How to study the past using dataQuantitative Analysis for Historical Social Science advances historical research in the social sciences by bridging the divide between qualitative and quantitative analysis. Gregory Wawro and Ira Katznelson argue for an expansion of the standard quantitative methodological toolkit with a set of innovative approaches that better capture nuances missed by more commonly used statistical methods. Demonstrating how to employ such promising tools, Wawro and Katznelson address the criticisms made by prominent historians and historically oriented social scientists regarding the shortcomings of mainstream quantitative approaches for studying the past.Traditional statistical methods have been inadequate in addressing temporality, periodicity, specificity, and context—features central to good historical analysis. To address these shortcomings, Wawro and Katznelson argue for the application of alternative approaches that are particularly well-suited to incorporating these features in empirical investigations. The authors demonstrate the advantages of these techniques with replications of research that locate structural breaks and uncover temporal evolution. They develop new practices for testing claims about path dependence in time-series data, and they discuss the promise and perils of using historical approaches to enhance causal inference.Opening a dialogue among traditional qualitative scholars and applied quantitative social scientists focusing on history, Quantitative Analysis for Historical Social Science illustrates powerful ways to move historical s
By addressing key criticisms of traditional statistical methods, Wawro and Katznelson introduce advanced techniques tailored to handle temporality, periodicity, specificity, and context—attributes essential for sound historical analysis. Unlock powerful insights as the authors exemplify these methods through replicative research that highlights structural breaks and temporal evolution. They also provide valuable practices for examining path dependence using time-series data, ultimately enhancing causal inference in historical studies.
Whether you are exploring historical patterns or conducting empirical investigations, *Quantitative Analysis for Historical Social Science* equips you with the knowledge needed to elevate your research approach. Shipping for this item is FREE, however, please allow 6 weeks for shipping. Kindly note, once you place the order, we are unable to cancel it. Perfect for academics and a valuable addition to your personal library, order your brand new copy today and delve into the innovative world of historical social science analysis.
Shipping for this item is FREE, however please allow 6 weeks for shipping, please note once you place the order we are not able to cancel it.
Condition: BRAND NEW
ISBN: 9780691155050
Format: Trade paperback (US)
Year: 2022
Publisher: Princeton University Press
Description:
How to study the past using dataQuantitative Analysis for Historical Social Science advances historical research in the social sciences by bridging the divide between qualitative and quantitative analysis. Gregory Wawro and Ira Katznelson argue for an expansion of the standard quantitative methodological toolkit with a set of innovative approaches that better capture nuances missed by more commonly used statistical methods. Demonstrating how to employ such promising tools, Wawro and Katznelson address the criticisms made by prominent historians and historically oriented social scientists regarding the shortcomings of mainstream quantitative approaches for studying the past.Traditional statistical methods have been inadequate in addressing temporality, periodicity, specificity, and context—features central to good historical analysis. To address these shortcomings, Wawro and Katznelson argue for the application of alternative approaches that are particularly well-suited to incorporating these features in empirical investigations. The authors demonstrate the advantages of these techniques with replications of research that locate structural breaks and uncover temporal evolution. They develop new practices for testing claims about path dependence in time-series data, and they discuss the promise and perils of using historical approaches to enhance causal inference.Opening a dialogue among traditional qualitative scholars and applied quantitative social scientists focusing on history, Quantitative Analysis for Historical Social Science illustrates powerful ways to move historical s