Testing Research Hypotheses Using Multiple Linear Regression

Testing Research Hypotheses Using Multiple Linear Regression
Author: Keith A. McNeil
Publisher:
Total Pages: 616
Release: 1975
Genre: Mathematics
ISBN:

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Multiple regression is becomingmore wide­ly used as the statistical technique for answering research hypotheses. This is so for several reasons: 1) the technique is extreme­ly versatile; 2) the computer has made the technique more available to researchers; and 3) texts such as the authors' earlier work are making the technique more available to re­searchers. The statistical technique of mul­tiple regression allows the inclusion of numerous continuous (quantitative) and categorical (qualitative) variables in the prediction of some criterion. Appendixes contain a multiple regression computer program and data on which the problems are based; a discussion of the simi­larities and differences between analysis of variance and multiple regression; and a computer program providing the regression solution to natural language research hy­potheses.

Applied Econometrics with R

Applied Econometrics with R
Author: Christian Kleiber
Publisher: Springer Science & Business Media
Total Pages: 229
Release: 2008-12-10
Genre: Business & Economics
ISBN: 0387773185

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R is a language and environment for data analysis and graphics. It may be considered an implementation of S, an award-winning language initially - veloped at Bell Laboratories since the late 1970s. The R project was initiated by Robert Gentleman and Ross Ihaka at the University of Auckland, New Zealand, in the early 1990s, and has been developed by an international team since mid-1997. Historically, econometricians have favored other computing environments, some of which have fallen by the wayside, and also a variety of packages with canned routines. We believe that R has great potential in econometrics, both for research and for teaching. There are at least three reasons for this: (1) R is mostly platform independent and runs on Microsoft Windows, the Mac family of operating systems, and various ?avors of Unix/Linux, and also on some more exotic platforms. (2) R is free software that can be downloaded and installed at no cost from a family of mirror sites around the globe, the Comprehensive R Archive Network (CRAN); hence students can easily install it on their own machines. (3) R is open-source software, so that the full source code is available and can be inspected to understand what it really does, learn from it, and modify and extend it. We also like to think that platform independence and the open-source philosophy make R an ideal environment for reproducible econometric research.

Testing Research Hypotheses with the General Linear Model

Testing Research Hypotheses with the General Linear Model
Author: Keith A. McNeil
Publisher: SIU Press
Total Pages: 400
Release: 1996
Genre: Mathematics
ISBN: 9780809320196

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Briefly describes 777 serial bibliographies relating to modern literature in most of the major languages. Chapters cover comprehensive bibliographies, those for English and foreign literatures, for topics from African American studies to women's studies, and for particular authors. The 1982 edition has been updated and expanded to include information on electronic serial bibliographies. Paper edition (unseen), $19.75. Annotation copyright by Book News, Inc., Portland, OR

Introduction to Econometrics

Introduction to Econometrics
Author: James H. Stock
Publisher: Prentice Hall
Total Pages: 0
Release: 2015
Genre: Econometrics
ISBN: 9780133486872

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For courses in Introductory Econometrics Engaging applications bring the theory and practice of modern econometrics to life. Ensure students grasp the relevance of econometrics with Introduction to Econometrics-the text that connects modern theory and practice with motivating, engaging applications. The Third Edition Update maintains a focus on currency, while building on the philosophy that applications should drive the theory, not the other way around. This program provides a better teaching and learning experience-for you and your students. Here's how: Personalized learning with MyEconLab-recommendations to help students better prepare for class, quizzes, and exams-and ultimately achieve improved comprehension in the course. Keeping it current with new and updated discussions on topics of particular interest to today's students. Presenting consistency through theory that matches application. Offering a full array of pedagogical features. Note: You are purchasing a standalone product; MyEconLab does not come packaged with this content. If you would like to purchase both the physical text and MyEconLab search for ISBN-10: 0133595420 ISBN-13: 9780133595420. That package includes ISBN-10: 0133486877 /ISBN-13: 9780133486872 and ISBN-10: 0133487679/ ISBN-13: 9780133487671. MyEconLab is not a self-paced technology and should only be purchased when required by an instructor.

Learning Statistics with R

Learning Statistics with R
Author: Daniel Navarro
Publisher: Lulu.com
Total Pages: 617
Release: 2013-01-13
Genre: Computers
ISBN: 1326189727

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"Learning Statistics with R" covers the contents of an introductory statistics class, as typically taught to undergraduate psychology students, focusing on the use of the R statistical software and adopting a light, conversational style throughout. The book discusses how to get started in R, and gives an introduction to data manipulation and writing scripts. From a statistical perspective, the book discusses descriptive statistics and graphing first, followed by chapters on probability theory, sampling and estimation, and null hypothesis testing. After introducing the theory, the book covers the analysis of contingency tables, t-tests, ANOVAs and regression. Bayesian statistics are covered at the end of the book. For more information (and the opportunity to check the book out before you buy!) visit http://ua.edu.au/ccs/teaching/lsr or http://learningstatisticswithr.com

The Use of Contrast Coefficients

The Use of Contrast Coefficients
Author: Ernest L. Lewis
Publisher:
Total Pages: 94
Release: 1978
Genre: Mathematics
ISBN:

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In addition to providing a direct appli­cation of the approach of McNeil, Kelly, and McNeil (Southern Illinois University Press, 1975), Ernest L. Lewis and John T. Mouw update the practice of multiple regression analysis and thus enhance the use of this popu­lar technique in applied research. Writ­ten and organized for the learner, this new work uses contrast coding pro­cedures which provide means for re­searchers in experimentally oriented statistics to run specific contrasts in multiple regression. As users of the McNeil, Kelly, and McNeil text will know, that work stressed representative research design. In supplementing the earlier work, Lewis and Mouw have developed a com­panion text providing the experimental design bias. The two texts taken to­gether give the content-oriented re­searcher an approach that is understand­able without sacrificing rigor or utility.

Multiple Regression

Multiple Regression
Author: Aki Roberts
Publisher: SAGE Publications
Total Pages: 190
Release: 2020-12-16
Genre: Social Science
ISBN: 1544358822

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Multiple Regression: A Practical Introduction is a text for an advanced undergraduate or beginning graduate course in statistics for social science and related fields. Also, students preparing for more advanced courses can self-study the text to refresh and solidify their statistical background. Drawing on decades of teaching this material, the authors present the ideas in an approachable and nontechnical manner, with no expectation that readers have more than a standard introductory statistics course as background. Multiple regression asks how a dependent variable is related to, or predicted by, a set of independent variables. The book includes many interesting example analyses and interpretations, along with exercises. Each dataset used for the examples and exercises is small enough for readers to easily grasp the entire dataset and its analysis with respect to the specific statistical techniques covered. A website for the book includes SPSS, Stata, SAS, and R code and commands for each type of analysis or recoding of variables in the book. Solutions to two of the end-of-chapter exercise types are also available for students to practice. The instructor side of the site contains editable PowerPoint slides, other solutions, and a test bank.

Linear Regression Analysis: Theory And Computing

Linear Regression Analysis: Theory And Computing
Author: Xin Yan
Publisher: World Scientific
Total Pages: 349
Release: 2009-06-05
Genre: Mathematics
ISBN: 9814470082

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This volume presents in detail the fundamental theories of linear regression analysis and diagnosis, as well as the relevant statistical computing techniques so that readers are able to actually model the data using the methods and techniques described in the book. It covers the fundamental theories in linear regression analysis and is extremely useful for future research in this area. The examples of regression analysis using the Statistical Application System (SAS) are also included. This book is suitable for graduate students who are either majoring in statistics/biostatistics or using linear regression analysis substantially in their subject fields.