Quantitative data analysis : doing social research to test ideas / Donald J. Treiman.

By: Treiman, Donald J
Material type: TextTextLanguage: English Publisher: San Francisco : Jossey-Bass, c2009Edition: 1st edDescription: xxxii, 443 p. : ill. ; 24 cmISBN: 9780470380031 (pbk. : alk. paper); 0470380039Other title: Doing social research to test ideasSubject(s): Social sciences -- Research -- Statistical methods | Sociology -- Research -- Statistical methodsDDC classification: 300.72 LOC classification: HA29 | .T675 2009Online resources: Table of contents only | WorldCat details | E-book Fulltext
Contents:
Table of contents Cross-tubulations -- More on tables -- Still more on tables -- On the manipulation of data by computer -- Introduction to correlation and regression (ordinary least squares) -- Introduction to multiple correlation and regressions (ordinary least squares) -- Multiple regression tricks: techniques for handling special analytic problems -- Multiple imputation of missing data -- Sample design and survey estimation -- Regression diagnostics -- Scale construction -- Log-linear analysis -- Bionomial logistic regression -- Multinomial and ordinal logistic regression and tobit regression -- Improving causal inference: fixed effects and random effects modeling -- Final thoughts and future directions: research design and interpretation issues.
Summary: Summary: This book is an accessible introduction to quantitative data analysis, concentrating on the key issues facing those new to research, such as how to decide which statistical procedure is suitable, and how to interpret the subsequent results.
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Includes bibliographical references and index.

Table of contents Cross-tubulations --
More on tables --
Still more on tables --
On the manipulation of data by computer --
Introduction to correlation and regression (ordinary least squares) --
Introduction to multiple correlation and regressions (ordinary least squares) --
Multiple regression tricks: techniques for handling special analytic problems --
Multiple imputation of missing data --
Sample design and survey estimation --
Regression diagnostics --
Scale construction --
Log-linear analysis --
Bionomial logistic regression --
Multinomial and ordinal logistic regression and tobit regression --
Improving causal inference: fixed effects and random effects modeling --
Final thoughts and future directions: research design and interpretation issues.

Summary:
This book is an accessible introduction to quantitative data analysis, concentrating on the key issues facing those new to research, such as how to decide which statistical procedure is suitable, and how to interpret the subsequent results.

Applied Statistics

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