Author: Robert Ho Publisher: CRC Press ISBN: 1439890226 Category : Mathematics Languages : en Pages : 600
Book Description
Using the same accessible, hands-on approach as its best-selling predecessor, the Handbook of Univariate and Multivariate Data Analysis with IBM SPSS, Second Edition explains how to apply statistical tests to experimental findings, identify the assumptions underlying the tests, and interpret the findings. This second edition now covers more topics
Author: Robert Ho Publisher: CRC Press ISBN: 1420011111 Category : Mathematics Languages : en Pages : 426
Book Description
Many statistics texts tend to focus more on the theory and mathematics underlying statistical tests than on their applications and interpretation. This can leave readers with little understanding of how to apply statistical tests or how to interpret their findings. While the SPSS statistical software has done much to alleviate the frustrations of s
Author: Robert Ho Publisher: CRC Press ISBN: 1439890218 Category : Mathematics Languages : en Pages : 588
Book Description
Using the same accessible, hands-on approach as its best-selling predecessor, the Handbook of Univariate and Multivariate Data Analysis with IBM SPSS, Second Edition explains how to apply statistical tests to experimental findings, identify the assumptions underlying the tests, and interpret the findings. This second edition now covers more topics and has been updated with the SPSS statistical package for Windows. New to the Second Edition Three new chapters on multiple discriminant analysis, logistic regression, and canonical correlation New section on how to deal with missing data Coverage of tests of assumptions, such as linearity, outliers, normality, homogeneity of variance-covariance matrices, and multicollinearity Discussions of the calculation of Type I error and the procedure for testing statistical significance between two correlation coefficients obtained from two samples Expanded coverage of factor analysis, path analysis (test of the mediation hypothesis), and structural equation modeling Suitable for both newcomers and seasoned researchers in the social sciences, the handbook offers a clear guide to selecting the right statistical test, executing a wide range of univariate and multivariate statistical tests via the Windows and syntax methods, and interpreting the output results. The SPSS syntax files used for executing the statistical tests can be found in the appendix. Data sets employed in the examples are available on the book’s CRC Press web page.
Author: Jan Jonker Publisher: Springer Science & Business Media ISBN: 3540716599 Category : Business & Economics Languages : en Pages : 171
Book Description
Methodology is the ?eld which is indisputably complex. In the academic world, it is often said to be important, yet in everyday academic practice, it is not always treated accordingly. In teaching, methodology is often a mandatory course. Usually, it consists of learning how to adopt several common approaches when doing research, and how to conceive a research design (often leading to a survey). This usually leads to collecting data on a modest scale and – when the opportunity arises – analysing the data with the help of some statistics. Ask the students of their opinion at the end of such a course and they tend to heave a deep sigh of relief and say, “I have got through it. ” Then their real courses start again, in which methodology often does not play a role at all. We are of the opinion that writing-off methodology in this way is a real pity. It ignores the valuable role that methodology should play in academic teaching as a whole. Here, methodology is presented as a form of thinking and acting that, while obviously entailing research work, can also include the design and change of organisations. This broad approach has been purposefully chosen, as it is almost obvious from research and graduation projects that the students do not really have a clue what methodology involves and, therefore, wasting their time by producing work that has a little quality.
Author: Daniel J. Denis Publisher: John Wiley & Sons ISBN: 1119465818 Category : Mathematics Languages : en Pages : 222
Book Description
Enables readers to start doing actual data analysis fast for a truly hands-on learning experience This concise and very easy-to-use primer introduces readers to a host of computational tools useful for making sense out of data, whether that data come from the social, behavioral, or natural sciences. The book places great emphasis on both data analysis and drawing conclusions from empirical observations. It also provides formulas where needed in many places, while always remaining focused on concepts rather than mathematical abstraction. SPSS Data Analysis for Univariate, Bivariate, and Multivariate Statistics offers a variety of popular statistical analyses and data management tasks using SPSS that readers can immediately apply as needed for their own research, and emphasizes many helpful computational tools used in the discovery of empirical patterns. The book begins with a review of essential statistical principles before introducing readers to SPSS. The book then goes on to offer chapters on: Exploratory Data Analysis, Basic Statistics, and Visual Displays; Data Management in SPSS; Inferential Tests on Correlations, Counts, and Means; Power Analysis and Estimating Sample Size; Analysis of Variance – Fixed and Random Effects; Repeated Measures ANOVA; Simple and Multiple Linear Regression; Logistic Regression; Multivariate Analysis of Variance (MANOVA) and Discriminant Analysis; Principal Components Analysis; Exploratory Factor Analysis; and Non-Parametric Tests. This helpful resource allows readers to: Understand data analysis in practice rather than delving too deeply into abstract mathematical concepts Make use of computational tools used by data analysis professionals. Focus on real-world application to apply concepts from the book to actual research Assuming only minimal, prior knowledge of statistics, SPSS Data Analysis for Univariate, Bivariate, and Multivariate Statistics is an excellent “how-to” book for undergraduate and graduate students alike. This book is also a welcome resource for researchers and professionals who require a quick, go-to source for performing essential statistical analyses and data management tasks.
Author: Daniel J. Denis Publisher: John Wiley & Sons ISBN: 1119549930 Category : Mathematics Languages : en Pages : 384
Book Description
A practical source for performing essential statistical analyses and data management tasks in R Univariate, Bivariate, and Multivariate Statistics Using R offers a practical and very user-friendly introduction to the use of R software that covers a range of statistical methods featured in data analysis and data science. The author— a noted expert in quantitative teaching —has written a quick go-to reference for performing essential statistical analyses and data management tasks in R. Requiring only minimal prior knowledge, the book introduces concepts needed for an immediate yet clear understanding of statistical concepts essential to interpreting software output. The author explores univariate, bivariate, and multivariate statistical methods, as well as select nonparametric tests. Altogether a hands-on manual on the applied statistics and essential R computing capabilities needed to write theses, dissertations, as well as research publications. The book is comprehensive in its coverage of univariate through to multivariate procedures, while serving as a friendly and gentle introduction to R software for the newcomer. This important resource: Offers an introductory, concise guide to the computational tools that are useful for making sense out of data using R statistical software Provides a resource for students and professionals in the social, behavioral, and natural sciences Puts the emphasis on the computational tools used in the discovery of empirical patterns Features a variety of popular statistical analyses and data management tasks that can be immediately and quickly applied as needed to research projects Shows how to apply statistical analysis using R to data sets in order to get started quickly performing essential tasks in data analysis and data science Written for students, professionals, and researchers primarily in the social, behavioral, and natural sciences, Univariate, Bivariate, and Multivariate Statistics Using R offers an easy-to-use guide for performing data analysis fast, with an emphasis on drawing conclusions from empirical observations. The book can also serve as a primary or secondary textbook for courses in data analysis or data science, or others in which quantitative methods are featured.
Author: Sabine Landau Publisher: Chapman & Hall/CRC ISBN: 9781138462496 Category : SPSS (Computer file) Languages : en Pages : 0
Book Description
Shows how to conduct a range of univariate and multivariate statistical analysis using the Statistical Package for the Social Sciences, version 11. This title addresses various types of analytical procedure that are applied to data sets, primarily from the social and behavioral sciences areas. It is suitable for researchers in psychology.
Author: Nancy L. Leech Publisher: Routledge ISBN: 1136760288 Category : Computers Languages : en Pages : 312
Book Description
Designed to help readers analyze and interpret research data using IBM SPSS, this user-friendly book shows readers how to choose the appropriate statistic based on the design, perform intermediate statistics, including multivariate statistics, interpret output, and write about the results. The book reviews research designs and how to assess the accuracy and reliability of data: whether data meet the assumptions of statistical tests; how to calculate and interpret effect sizes for intermediate statistics, including odds ratios for logistic and discriminant analyses; how to compute and interpret post-hoc power; and an overview of basic statistics for those who need a review. Unique chapters on multilevel linear modeling, multivariate analysis of variance (MANOVA), assessing reliability of data, and factor analysis are provided. SPSS syntax, along with the output, is included for those who prefer this format. The new edition features: IBM SPSS version 19; although the book can be used with most older and newer versions expanded discussion of assumptions and effect size measures in several chapters expanded discussion of multilevel modeling expansion of other useful SPSS functions in Appendix A examples that meet the new formatting guidelines in the 6th edition of the APA Publication Manual (2010) flowcharts and tables to help select the appropriate statistic and interpret statistical significance and effect sizes multiple realistic data sets available on the website used to solve the chapter problems password protected Instructor's Resource materials with PowerPoint slides, answers to interpretation questions and extra SPSS problems, and chapter outlines and study guides. IBM SPSS for Intermediate Statistics, Fourth Edition provides helpful teaching tools: all of the key SPSS windows needed to perform the analyses outputs with call-out boxes to highlight key points interpretation sections and questions to help students better understand and interpret the output extra problems using multiple realistic data sets for practice in conducting analyses using intermediate statistics helpful appendices on how to get started with SPSS, writing research questions, and review of basic statistics. An ideal supplement for courses in either intermediate/advanced statistics or research methods taught in departments of psychology, education, and other social and health sciences, this book is also appreciated by researchers in these areas looking for a handy reference for SPSS.
Author: Daniel J. Denis Publisher: John Wiley & Sons ISBN: 1118632311 Category : Mathematics Languages : en Pages : 760
Book Description
A clear and efficient balance between theory and application of statistical modeling techniques in the social and behavioral sciences Written as a general and accessible introduction, Applied Univariate, Bivariate, and Multivariate Statistics provides an overview of statistical modeling techniques used in fields in the social and behavioral sciences. Blending statistical theory and methodology, the book surveys both the technical and theoretical aspects of good data analysis. Featuring applied resources at various levels, the book includes statistical techniques such as t-tests and correlation as well as more advanced procedures such as MANOVA, factor analysis, and structural equation modeling. To promote a more in-depth interpretation of statistical techniques across the sciences, the book surveys some of the technical arguments underlying formulas and equations. Applied Univariate, Bivariate, and Multivariate Statistics also features Demonstrations of statistical techniques using software packages such as R and SPSS® Examples of hypothetical and real data with subsequent statistical analyses Historical and philosophical insights into many of the techniques used in modern social science A companion website that includes further instructional details, additional data sets, solutions to selected exercises, and multiple programming options An ideal textbook for courses in statistics and methodology at the upper- undergraduate and graduate-levels in psychology, political science, biology, sociology, education, economics, communications, law, and survey research, Applied Univariate, Bivariate, and Multivariate Statistics is also a useful reference for practitioners and researchers in their field of application. DANIEL J. DENIS, PhD, is Associate Professor of Quantitative Psychology at the University of Montana where he teaches courses in univariate and multivariate statistics. He has published a number of articles in peer-reviewed journals and has served as consultant to researchers and practitioners in a variety of fields.
Author: Robert Ho
Author: Robert Ho
Author: Robert Ho
Author: Robert Ho
Author: Jan Jonker
Author: Daniel J. Denis
Author: Daniel J. Denis
Author: Sabine Landau
Author: Nancy L. Leech
Author: Daniel J. Denis