Higher education policy analysis using quantitative techniques : data, methods and presentation /

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Bibliographic Details
Author / Creator:Titus, Marvin.
Imprint:Cham, Switzerland : Springer, 2021.
Description:1 online resource
Language:English
Series:Quantitative Methods in the Humanities and Social Sciences, 2199-0956
Quantitative methods in the humanities and social sciences,
Subject:
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/12612938
Hidden Bibliographic Details
ISBN:9783030608316
303060831X
3030608301
9783030608309
Notes:Includes bibliographical references and index.
Online resource; title from PDF title page (SpringerLink, viewed May 24, 2021).
Summary:This textbook introduces graduate students in education and policy research to data and statistical methods in state-level higher education policy analysis. It also serves as a methodological guide to students, practitioners, and researchers who want a clear approach to conducting higher education policy analysis that involves the use of institutional- and state-level secondary data and quantitative methods ranging from descriptive to advanced statistical techniques. This book is unique in that it introduces readers to various types of data sources and quantitative methods utilized in policy research and in that it demonstrates how results of statistical analyses should be presented to higher education policy makers. It helps to bridge the gap between researchers, policy makers, and practitioners both within education policy and between other fields. Coverage includes identifying pertinent data sources, the creation and management of customized data sets, teaching beginning and advanced statistical methods and analyses, and the presentation of analyses for different audiences (including higher education policy makers).
Other form:Print version: 3030608301 9783030608309
Standard no.:10.1007/978-3-030-60831-6
Table of Contents:
  • 1. Introduction
  • 2. Asking and answering policy questions
  • 3. Identifying data sources and creating custom datasets
  • 4. Managing data
  • 5. Getting to know hy data
  • 6. Using descriptive statistics and graphs
  • 7. Introducing intermediate statistical methods
  • 8. Introducing advanced statistical methods
  • 9. Presenting the analysis to higher education policy makers
  • 10. Conclusion.