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Applied statistics I : basic bivariate techniques / Rebecca M. Warner, Professor Emerita, University of New Hampshire.

By: Warner, Rebecca M [author.].
Material type: materialTypeLabelBookPublisher: Los Angeles : SAGE, [2021]Copyright date: ©2021Edition: Third edition.Description: 1 online resource (xxiii, 623 pages) : illustrations ; 25 cm.Content type: text Media type: unmediated Carrier type: volumeSubject(s): Social sciences -- Statistical methods | Psychology -- Statistical methods | Multivariate analysisDDC classification: 519.535 Summary: "Applied Statistics I: Basic Bivariate Techniques has been created from the first half of Rebecca M. Warner's popular Applied Statistics: From Bivariate Through Multivariate Techniques. The author's contemporary approach differs from some of the well-worn texts in the market, and reflects current thinking in the field. It spends less time on statistical significance testing, and moves in the direction of the "new statistics" by focusing more on confidence intervals and effect size. Instructors of upper undergraduate or beginning graduate level courses will find that the greater focus on basic concepts such as partition of variance and effect size is more useful to students, particularly as preparation for more advanced courses. Spending less time on statistical significance testing allows for more time to be devoted to more interesting and useful statistics that students will see in journal articles (such as correlation and regression). This introductory statistics text includes examples in SPSS, together with datasets on an accompanying website. A companion study guide reproducing the exercises and examples in R will also be available"-- Provided by publisher.
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Current location Call number Status Notes Date due Item holds
University of Santo Tomas-Legazpi Main Library
Circulation
Circ. HA 31.35 .W37 2021 (Browse shelf) Available JB
Total holds: 0

Revised edition of the author's Applied statistics, c2013.

Includes bibliographical references and index.

"Applied Statistics I: Basic Bivariate Techniques has been created from the first half of Rebecca M. Warner's popular Applied Statistics: From Bivariate Through Multivariate Techniques. The author's contemporary approach differs from some of the well-worn texts in the market, and reflects current thinking in the field. It spends less time on statistical significance testing, and moves in the direction of the "new statistics" by focusing more on confidence intervals and effect size. Instructors of upper undergraduate or beginning graduate level courses will find that the greater focus on basic concepts such as partition of variance and effect size is more useful to students, particularly as preparation for more advanced courses. Spending less time on statistical significance testing allows for more time to be devoted to more interesting and useful statistics that students will see in journal articles (such as correlation and regression). This introductory statistics text includes examples in SPSS, together with datasets on an accompanying website. A companion study guide reproducing the exercises and examples in R will also be available"-- Provided by publisher.

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