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- #Pasw statistics 18 guide to data analysis how to
- #Pasw statistics 18 guide to data analysis software
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#Pasw statistics 18 guide to data analysis software
This unique combination of examples, exercises, and contemporary data gives you hands-on experience in analyzing data and makes learning about data analysis and statistical software relevant, unintimidating, and even fun!Ī data CD-ROM is included with this book. The SPSS 17.0 Guide to Data Analysis is a friendly introduction to both data analysis and SPSS, the world’s leading desktop statistical software package.
#Pasw statistics 18 guide to data analysis how to
With this book, you’ll learn how to describe data, test hypotheses, and examine relationships using PASW.Īuthor Marija Norušis incorporates a wealth of real data, including the General Social Survey and studies of Internet usage, opinions of the criminal justice system, marathon running times, library patronage, and the importance of manners, throughout the examples and expanded chapter exercises. PASW Statistics 18 Guide to Data Analysis 13.01 Only 1 left in stock - order soon. Easy-to-understand explanations and in-depth content make this guide both an excellent supplement to other statistics texts and a superb primary text for any introductory data analysis course. A companion website includes downloadable versions of all the data sets used in the book.The PASW Statistics 18 Guide to Data Analysis is a friendly introduction to both data analysis and PASW Statistics 18 (formerly SPSS Statistics), the world’s leading desktop statistical software package. Appendices show how to estimate the models in SAS, SPSS, and R provide a review of regression assumptions using simulations and discuss missing data. Each chapter discusses how to utilize the models and test their assumptions with the statistical software Stata, and also includes exercise sets so readers can practice using these techniques.
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The chapters address logistic and probit models, including those designed for ordinal and nominal variables, regular and zero-inflated Poisson and negative binomial models, event history models, models for longitudinal data, multilevel models, and data reduction techniques such as principal components and factor analysis. Numerous examples from the social sciences demonstrate the practical applications of these models. This book provides an introduction and overview of several statistical models designed for these types of outcomes-all presented with the assumption that the reader has only a good working knowledge of elementary algebra and has taken introductory statistics and linear regression analysis. Instead, they must measure and analyze these events and phenomena in a discrete manner. Another textbook, PASW Statistics 18 Guide to Data Analysis by Marija J. Sociologists examining the likelihood of interracial marriage, political scientists studying voting behavior, criminologists counting the number of offenses people commit, health scientists studying the number of suicides across neighborhoods, and psychologists modeling mental health treatment success are all interested in outcomes that are not continuous. SPSS stands for Statistical Package for the Social Sciences and it is powerful. Social science and behavioral science students and researchers are often confronted with data that are categorical, count a phenomenon, or have been collected over time. Given the breadth of its coverage, the textbook is suitable for introductory statistics, survey research or quantitative methods classes in the social sciences. In addition, it provides clear instructions on how to conduct the tests in SPSS and Stata. The book explains the theory, rationale and mathematical foundations of these tests. The Base add-on module must be used with the PASW Statistics 18 Core system and is completely integrated into that system. The Base optional add-on module provides the additional analytic techniques described in this manual. Lastly, they use said data to test their hypotheses in a bivariate and multivariate realm. PASW Statistics 18 is a comprehensive system for analyzing data. Students are shown how to create their own questionnaire based on some theoretically derived hypotheses to achieve empirical findings for a solid dataset. In detail, the textbook introduces students to the four pillars of survey research and quantitative analysis: (1) the importance of survey research, (2) preparing a survey, (3) conducting a survey and (4) analyzing a survey. Building on the premise that statistical methods need to be learned in a practical fashion, the book guides students through the various steps of the survey research process and helps to apply those steps toward a real example.
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This textbook offers an essential introduction to survey research and quantitative methods.