Making History Count
A Primer in Quantitative Methods for Historians
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This authoritative guide to the use of quantitative methods is designed to be used as the basic text for graduate courses, and is also suitable for upper-level students. Making History Count is written by two senior economic historians with considerable international teaching experience. The text is clearly illustrated with numerous tables, graphs and diagrams, leading the student through the various key topics. It is supported by five specific historical data-sets, available electronically in downloadable and manipulable form.Read more
- Major new text on core technique in economic and social history by world-class author team
- Does not require more than basic arithmetic
- Innovative use of supporting website, to permit manipulation of data in various exercises
Reviews & endorsements
"...no competitor text is, to my knowledge, as effective in taking the student from the basics of descriptive statistics through to the intricacies of multiple linear regression." Roger Middleton, University of BristolSee more reviews
"Feinstein and Thomas present basic statistical techniques based primarily on intuitive understanding and application of concepts aimed at mathematically sophisticated readers. The material is presented with great clarity.... Recommended." Choice
"The best textbook on statistical methods ever written for a historical audience." J. Morgan Kousser, California Institute of Technology
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- Date Published: August 2006
- format: Adobe eBook Reader
- isbn: 9780511074875
- contains: 1 table
- availability: This ISBN is for an eBook version which is distributed on our behalf by a third party.
Table of Contents
Part I. Elementary Statistical Analysis:
2. Descriptive statistics
4. Simple linear regression
Part II. Samples and Inductive Statistics:
5. Standard errors and confidence intervals
6. Hypothesis testing
7. Non-parametric tests
Part III. Multiple Linear Regression:
8. Multiple relationships
9. The classical linear regression model
10. Dummy variables and lagged values
Part IV. Further Topics in Regression Analysis:
11. Violating the assumptions of the classical model
12. Non-linear models and functional forms
13. Logit, probit, and tobit models
Part V. Specifying and Interpreting Models: Four Case Studies:
14. Case studies 1 and 2: unemployment in Britain and emigration from Ireland
15. Case studies 3 and 4: the Old Poor Law in England and leaving home in the United States, 1850–60
Appendix A. The four data sets
Appendix B. Index numbers
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