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Analysing quantitative data : variable-based and case-based approaches to non-experimental datasets / Raymond Kent.

By: Material type: TextTextPublisher: Los Angeles : Sage, [2015]Copyright date: ©2015Description: xxii, 349 pages : illustrations ; 25 cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 9781446273401 (hardcover)
  • 1446273407 (hardcover)
  • 9781446273418 (paperback)
  • 1446273415 (paperback)
Subject(s): DDC classification:
  • 300.7/21 23
LOC classification:
  • H62 .K4176 2015
Contents:
Part I. Quantitative data : structure, preparation and analysis approaches : 1. Data structure -- 2. Data preparation -- 3. Approaches to data analysis -- part II. Variable-based analyses : 4. Univariate analysis -- 5. Bivariate analysis -- 6. Multivariate analysis -- part III. Case-based analyses : 7. Set-theoretic methods and configurational data analysis -- 8. Cluster and discriminant analysis -- part IV. Comparing and communicating results : 9. Comparing and mixing methods -- 10. Evaluating hypotheses, explaining and communicating results.
Summary: "This innovative book provides a fresh take on quantitative data analysis within the social sciences. Using multidisciplinary non-experimental datasets it demonstrates that data analysis is really an active dialogue between ideas and evidence, between research objectives and data in a dataset." -- Cover.
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Item type Current library Call number Copy number Status Barcode
Books like text book referance book Books like text book referance book Social Library General Stacks 300.721KEN (Browse shelf(Opens below)) 1 Available SHLIB00012365

Includes bibliographical references (pages 343-346) and index.

Part I. Quantitative data : structure, preparation and analysis approaches : 1. Data structure -- 2. Data preparation -- 3. Approaches to data analysis -- part II. Variable-based analyses : 4. Univariate analysis -- 5. Bivariate analysis -- 6. Multivariate analysis -- part III. Case-based analyses : 7. Set-theoretic methods and configurational data analysis -- 8. Cluster and discriminant analysis -- part IV. Comparing and communicating results : 9. Comparing and mixing methods -- 10. Evaluating hypotheses, explaining and communicating results.

"This innovative book provides a fresh take on quantitative data analysis within the social sciences. Using multidisciplinary non-experimental datasets it demonstrates that data analysis is really an active dialogue between ideas and evidence, between research objectives and data in a dataset." -- Cover.

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