Theses and Dissertations: A Guide to Writing in the Social and Physical Sciences

This practical volume is designed to assist graduate students in planning, conducting, and writing theses or dissertations in the social and physical sciences. Numerous examples are provided and many tips are included to facilitate completion of the thesis or dissertation.

Politics & Social Sciences

McNeil, Keith

Newman, Isadore

Benz, Carolyn R.

Weis, David

Social Sciences

University Press of America

This practical volume is designed to assist graduate students in planning, conducting, and writing theses or dissertations in the social and physical sciences. Numerous examples are provided and many tips are included to facilitate completion of the thesis or dissertation.

Conducting Survey Research in the Social Sciences presents basic concepts and general guidelines for those who are interested in conducting a survey by breaking the process down into eight steps and twenty-three questions. It outlines the appropriate sequential steps necessary to help the reader initiate and develop a survey. Following each of the eight steps as depicted in the eight chapters and answering the questions provided enables the creation of an effective survey. The authors also include three fictitious vignettes to illustrate how the decisions should be made, and how proper survey research should be conducted to meet many different needs.

Conducting Survey Research in the Social Sciences

The focus of this text is placed on designing General Linear Models (regression models) to test research hypotheses. The authors illustrate and discuss General Linear Models specifically designed to statistically test research hypotheses that deal with the differences among group means, relationships between continuous variables, analysis of covariance, interaction effects, nonlinear relationships, and repeated measures. Many of the chapters contain sections entitled “General Hypothesis” and “Applied Hypothesis.” The General Hypothesis sections are designed to provide the readers with “road maps” regarding how to conduct the various analyses presented in the text. The Applied Hypothesis sections illustrate how the various analyses are conducted with Microsoft Excel and SPSS for Windows and how the outputs should be interpreted to test the hypotheses. Throughout the text, the authors stress the importance of designing regression models that precisely reflect the null and research hypotheses.

Designing General Linear Models to Test Research Hypotheses

Business & Money

Fraas, John W.

Industries

Testing Research Hypotheses with the General Linear Model

Because the technique of multiple linear regression has been accepted by the research community since 1975, Keith McNeil, Isadore Newman, and Francis J. Kelly devote little space to defending the equivalence of correlational and ANOVA procedures with multiple linear regression. Instead, they show how the multiple linear regression technique frees the researcher from wondering if an analysis can be done and refocuses him or her back to the central concern: the research question itself.The first three sections of chapter 1 provide a conceptual, research, and statistical orientation to the entire text. The remainder of chapter 1 furnishes the rationale for the utility of a conceptual model of behavior, along with one such model that can be used to identify predictor variables. The authors strongly suggest that readers familiar with the general linear model read these three sections before delving into the more advanced material. Readers who are relatively unfamiliar with the general linear model should read the first eight chapters before branching off into topics that are of immediate interest.Examples are provided throughout the text, all using the same data in the same widely available statistical analysis package. Although the technique can be taught with matrix algebra, the authors use the simpler approach of vector algebra, an approach more in line with the way data are conceptualized and entered into the computer.All of the correlational statistical techniques are shown to be subsets of the general linear model. Of more importance, however, researchers are encouraged to think beyond these limitations and to ask the research questions they are interested in. Thus, the common researcher is freed from the shackles of the "right" statistical procedure and its associated "right" computer analysis.

McNeil PhD, Keith

Kelly, Francis J.

Reference

Southern Illinois University Press

Because the technique of multiple linear regression has been accepted by the research community since 1975, Keith McNeil, Isadore Newman, and Francis J. Kelly devote little space to defending the equivalence of correlational and ANOVA procedures with multiple linear regression. Instead, they show how the multiple linear regression technique frees the researcher from wondering if an analysis can be done and refocuses him or her back to the central concern: the research question itself.
The first three sections of chapter 1 provide a conceptual, research, and statistical orientation to the entire text. The remainder of chapter 1 furnishes the rationale for the utility of a conceptual model of behavior, along with one such model that can be used to identify predictor variables. The authors strongly suggest that readers familiar with the general linear model read these three sections before delving into the more advanced material. Readers who are relatively unfamiliar with the general linear model should read the first eight chapters before branching off into topics that are of immediate interest.
Examples are provided throughout the text, all using the same data in the same widely available statistical analysis package. Although the technique can be taught with matrix algebra, the authors use the simpler approach of vector algebra, an approach more in line with the way data are conceptualized and entered into the computer.
All of the correlational statistical techniques are shown to be subsets of the general linear model. Of more importance, however, researchers are encouraged to think beyond these limitations and to ask the research questions they are interested in. Thus, the common researcher is freed from the shackles of the "right" statistical procedure and its associated "right" computer analysis.

In this book, authors Carolyn S. Ridenour and Isadore Newman reject the artificial dichotomy between qualitative and quantitative research strategies in the social and behavioral sciences and argue that by employing multiple methods, researchers can enhance the quality of their research outcomes.

Mixed Methods Research: Exploring the Interactive Continuum

Ridenour, Carolyn S.

This new edition emphasizes and facilitates the conceptual understanding of statistics and statistical concepts for the purpose of reading and accurately interpreting research literature. The use of hand calculators is deemphasized. Instead, computer example setups are supplied for Spss and Sas.

Conceptual Statistics for Beginners, Second Edition

Science & Math

Mathematics

38-22-36: Conceptual statistics for beginners

I. Newman

See the best price to sell, buy, or rent books by Newman, Isadore. BookScouter helps to compare book prices from 25+ online bookstores and 30+ buyback vendors with a single search.

Books by Newman, Isadore

See the best price to sell, buy, or rent books by Newman, Isadore. BookScouter helps to compare book prices from 25+ online bookstores and 30+ buyback vendors with a single search.

Theses and Dissertations: A Guide to Writing in the Social and Physical Sciences

Theses and Dissertations: A Guide to Writing in the Social and Physical Sciences

Conducting Survey Research in the Social Sciences

Designing General Linear Models to Test Research Hypotheses

Testing Research Hypotheses with the General Linear Model

Testing Research Hypotheses with the General Linear Model

Mixed Methods Research: Exploring the Interactive Continuum

Conceptual Statistics for Beginners, Second Edition

38-22-36: Conceptual statistics for beginners