Interpreting and Using Regression sets out the actual procedures researchers employ, places them in the framework of statistical theory, and shows how good research takes account both of statistical theory and real world demands. Achen builds a working philosophy of regression that goes well beyond the abstract, unrealistic treatment given in previous texts.
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2 of 2 people found the following review helpful:
5.0 out of 5 stars
An introductary text,
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This review is from: Interpreting and Using Regression (Quantitative Applications in the Social Sciences) (Paperback)
Although Achen's work has been written in 1982, before the booming computer packages and the dawn of internet age, the text is straightforward and grants the readers an adequate coverage on the techniques of regressions.
4.0 out of 5 stars
Practical and accessible guide,
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This review is from: Interpreting and Using Regression (Quantitative Applications in the Social Sciences) (Paperback)
"Interpreting and Using Regression" is a practical introductory guide that explains regression analysis and how to interpret the results. The text is written in plain English. Achen offers easy-to-understand examples and analogies to illustrate the concepts and procedures in this short (but unfortunately expensive) book. His book is an excellent introduction to regression, as well as a helpful companion to more advanced texts when conducting statistical research.
0 of 9 people found the following review helpful:
2.0 out of 5 stars
interpreting and using regression,
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This review is from: Interpreting and Using Regression (Quantitative Applications in the Social Sciences) (Paperback)
I need to find how to do regression analysis on SPSS with many different kind variables (how to prepare for analysis e.g. preparing dummy variables, selecting variables, selecting type of process <enter, forward, backward> and interprete them. I am not a statistican, I don't need statistical explanation. I only need practical way to use this method appropriately, but I can not find my needs. It would be helpful for reeders if there is short summary of books,
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Inside This Book
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First Sentence:
Statistical theory is a branch of mathematics. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
causal strength, vote difference, social science applications, cube law, standardized betas, alternate hypotheses, substantive significance Key Phrases - Capitalized Phrases (CAPs): (learn more)
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Statistical theory is a branch of mathematics. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
causal strength, vote difference, social science applications, cube law, standardized betas, alternate hypotheses, substantive significance Key Phrases - Capitalized Phrases (CAPs): (learn more)
Union Leader, New Hampshire, United States New!
Books on Related Topics | Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Back Cover | Surprise Me!
Citations (learn more)
This book cites 76
books:
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100
books
cite this book:
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- Southern Politics by Valdimer Orlando Key on page 11, and Back Matter
- Southern Politics in State and Nation by V.O. Key on page 11, and Back Matter
- Research Designs (Quantitative Applications in the Social Sciences) by Paul E. Spector in Back Matter
- Three Essays on the State of Economic Science (Reprints of Economic Classics) by Tjalling Charles Koopmans in Back Matter
- Who Votes? (Yale Fastback Series) by Raymond E. Wolfinger in Back Matter
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- Chaos and Catastrophe Theories (Quantitative Applications in the Social Sciences) by Courtney Brown in Back Matter (1), Back Matter (2), and Back Matter (3)
- Multiple Regression in Practice (Quantitative Applications in the Social Sciences) by William D. Berry in Front Matter, and Back Matter
- Test Item Bias (Quantitative Applications in the Social Sciences) by Steven J. Osterlind in Back Matter (1), and Back Matter (2)
- The Comparative Political Economy of the Welfare State (Cambridge Studies in Comparative Politics) by Thomas Janoski on page 50, and page 88
- Linear Probability, Logit, and Probit Models (Quantitative Applications in the Social Sciences) by John H. Aldrich in Back Matter (1), and Back Matter (2)
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