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Understanding Educational Statistics Using Microsoft Excel and SPSS von Abbott, Martin Lee (eBook)

  • Erscheinungsdatum: 21.08.2014
  • Verlag: Wiley
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Understanding Educational Statistics Using Microsoft Excel and SPSS

Utilizing the latest software, this book presents the essential statistical procedures for drawing valuable results from data in the social sciences. Mobilizing interesting real-world examples from the field of education, Understanding Educational Statistics Using Microsoft Excel and SPSS supplies a seamless presentation that identifies valuable connections between statistical applications and research design. Class-tested to ensure an accessible presentation, the book combines clear, step-by-step explanations and the use of software packages that are accessible to both the novice and professional alike to present the fundamental statistical practices for organizing, understanding, and drawing conclusions from educational research data. The book begines with an introduction to descriptive and inferential statistics and then proceeds to acquaint readers with the various functions for working with quantitative data in the Microsoft Excel environment, such as spreadsheet navigation; sorting and filtering; and creating pivot tables. Subsequent chapters treat the procedures that are commonly-employed when working with data across various fields of social science research, including: Single-sample tests Repeated measure tests Independent t-tests One way ANOVA and factorial ANOVA Correlation Bivariate regression Chi square Multiple regression
Individual chapters are devoted to specific procedures, each ending with a lab exercise that highlights the importance of that procedure by posing a research question, examining the question through its application in Excel and SPSS, and concluding with a brief research report that outlines key findings drawn from the results. Real-world examples and data from modern educational research are used throughout the book, and a related Web site features additional data sets, examples, and labs, allowing readers to reinforce their comprehension of the material. Bridging traditional statistical topics with the latest software and applications in the field of education, Understanding Educational Statistics Using Microsoft Excel and SPSS is an excellent book for courses on educational research methods and introductory statistics in the social sciences at the upper-undergraduate and graduate levels. It also serves as a valuable resource for researchers and practitioners in the fields of education, psychology, and the social sciences who require a statistical background to work with data in their everyday work. MARTIN LEE ABBOTT , PhD, is Professor of Sociology at Seattle Pacific University, where he also serves as Executive Director of the Washington School Research Center, an independent research and data analysis center funded by the Bill and Melinda Gates Foundation. He has held positions in both academia and in industry, focusing his consulting and teaching in the areas of program evaluation, applied sociology, statistics, and research methods. Dr. Abbott is the author of The Program Evaluation Prism: Using Statistical Methods to Discover Patterns (Wiley).


    Format: ePUB
    Kopierschutz: AdobeDRM
    Seitenzahl: 552
    Erscheinungsdatum: 21.08.2014
    Sprache: Englisch
    ISBN: 9781118627181
    Verlag: Wiley
    Größe: 9065 kBytes
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Understanding Educational Statistics Using Microsoft Excel and SPSS



Many students and researchers are intimidated by statistical procedures. This may in part be due to a fear of math, problematic math teachers in earlier education, or the lack of exposure to a "discovery" method for understanding difficult procedures. Readers of this book should realize that they have the ability to succeed in understanding statistical processes.

This is an introduction to statistics using EXCEL® and SPSS® to make it more understandable. Ordinarily, the first course leads the student through the worlds of descriptive and inferential statistics by highlighting the formulas and sequential procedures that lead to statistical decision making. We will do all this in this book, but I place a good deal more attention on conceptual understanding. Thus, rather than memorizing a specific formula and using it in a specific way to solve a problem, I want to make sure the student first understands the nature of the problem, why a specific formula is needed, and how it will result in the appropriate information for decision making.

By using statistical software, we can place more attention on understanding how to interpret findings . Statistics courses taught in mathematics departments, and in some social science departments, often place primary emphases on the formulas/ processes themselves. In the extreme, this can limit the usefulness of the analyses to the practitioner. My approach encourages students to focus more on how to understand and make applications of the results of statistical analyses. EXCEL® and other statistical programs are much more efficient at performing the analyses; the key issue in my approach is how to interpret the results in the context of the research question.

Beginning with my first undergraduate course through teaching statistics with conventional textbooks, I have spent countless hours demonstrating how to conduct statistical tests by hand and teaching students to do likewise. This is not always a bad strategy; performing the analysis by hand can lead the student to understand how formulas treat data and yield valuable information. However, it is often the case that the student gravitates to memorizing the formula or the steps in an analysis. Again, there is nothing wrong with this approach as long as the student does not stop there. The outcome of the analysis is more important than memorizing the steps to the outcome. Examining the appropriate output derived from statistical software shifts the attention from the nuances of a formula to the wealth of information obtained by using it.

It is important to understand that I do indeed teach the student the nuances of formulas, understanding why, when, how, and under what conditions they are used. But in my experience, forcing the student to scrutinize statistical output files accomplishes this and teaches them the appropriate use and limitations of the information derived.

Students in my classes are always surprised (ecstatic) to realize they can use their textbooks, notes, and so on, on my exams. But they quickly find that, unless they really understand the principles and how they are applied and interpreted, an open book is not going to help them. Over time, they come to realize that the analyses and the outcomes of statistical procedures are simply the ingredients for what comes next: building solutions to research problems. Therefore, their role is more detective and constructor than number juggler.

This approach mirrors the recent national and international debate about math pedagogy. In my recent book, Winning the Math Wars (Abbott et al., 2010), my colleagues and I addressed these issues in great detail, suggesting that, while traditional ways of teaching math are useful and important, the emphases of reform approaches are not to be dismissed. Understanding and memorizing de

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