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Making History Count

Making History Count

Making History Count

A Primer in Quantitative Methods for Historians
Charles H. Feinstein, University of Oxford
Mark Thomas, University of Virginia
October 2002
Paperback
9780521001373
$78.99
USD
Paperback
USD
eBook

    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.

    • 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 Bristol

    "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

    See more reviews

    Product details

    October 2002
    Paperback
    9780521001373
    572 pages
    256 × 178 × 40 mm
    1.258kg
    1 table
    Available

    Table of Contents

    • Part I. Elementary Statistical Analysis:
    • 1. Introduction
    • 2. Descriptive statistics
    • 3. Correlation
    • 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
    • Index.
    Resources for
    Type
    8. Local Unemployment in Great Britain, 1929: CSV File
    Size: 3.39 KB
    Type: text/csv
    8. Local Unemployment in Great Britain, 1929: Excel Spreadsheet
    Size: 35.5 KB
    Type: application/vnd.ms-excel
    6. Leaving Home in the United States: SPSS File
    Size: 16.85 KB
    Type: application/octet-stream
    3. Panel dataset: SPSS File
    Size: 15.13 KB
    Type: application/octet-stream
    1. Unemployment in Britain: CSV File
    Size: 1.26 KB
    Type: text/csv
    1. Unemployment in Britain: Excel Spreadsheet
    Size: 14.5 KB
    Type: application/vnd.ms-excel
    1. Unemployment in Britain: Minitab File
    Size: 1.34 KB
    Type: application/octet-stream
    5. Relief dataset: Minitab File
    Size: 23.84 KB
    Type: application/octet-stream
    3. Panel dataset: STATA File
    Size: 9.33 KB
    Type: application/octet-stream
    2. Emigration from Ireland: CSV File
    Size: 4.33 KB
    Type: text/csv
    3. Panel dataset: Excel Spreadsheet
    Size: 34 KB
    Type: application/vnd.ms-excel
    1. Unemployment in Britain: SPSS File
    Size: 1.68 KB
    Type: application/octet-stream
      Authors
    • Charles H. Feinstein , University of Oxford
    • Mark Thomas , University of Virginia