Guided by problems that frequently arise in actual practice, James Higgins’ book presents a wide array of nonparametric methods of data analysis that researchers will find useful. It discusses a variety of nonparametric methods and, wherever possible, stresses the connection between methods. For instance, rank tests are introduced as special cases of permutation tests applied to ranks. The author provides coverage of topics not often found in nonparametric textbooks, including procedures for multivariate data, multiple regression, multi-factor analysis of variance, survival data, and curve smoothing. This truly modern approach teaches non-majors how to analyze and interpret data with nonparametric procedures using today’s computing technology.
This companion is designed for anyone who desires a guide to using SAS to carry out nonparametric analyses. It can serve as a SAS lab manual for students enrolled in a course covering nonparametric methods where SAS is used for computing. It is also an excellent reference for researchers who currently use SAS and wish to learn about the capabilities of SAS for performing nonparametric analyses and the syntax for implementing the procedures. An important feature of this companion is that all of the SAS examples presented are self-contained and can be entered into SAS, as they appear, and executed. Thus, the user does not have to deal with issues of creating SAS data sets before using the programs. In addition to presenting the SAS code to obtain various nonparametric analyses, brief introductions to the methods themselves are also given. Particular attention is given to how SAS calculates the results it presents, and explanation provided wherever SAS presents results that might be different from what is typically presented in textbooks.
MODERN BUSINESS STATISTICS, 5E allows students to gain a strong conceptual understanding of statistics with a balance of real-world applications and a focus on the integrated strengths of Microsoft Excel 2013. To ensure student understanding, this best-selling, comprehensive text carefully discusses and clearly develops each statistical technique in a solid application setting. Microsoft Excel 2013 instruction, which is integrated in each chapter, plays an integral part in strengthening this edition's applications orientation. Immediately after each easy-to-follow presentation of a statistical procedure, a subsection discusses how to use Excel to perform the procedure. This integrated approach emphasizes the applications of Excel while focusing on the statistical methodology. Step-by-step instructions and screen captures further clarify student learning. A wealth of timely business examples, proven methods, and additional exercises throughout this edition demonstrate how statistical results provide insights into business decisions and present solutions to contemporary business problems. High-quality problems noted for their unwavering accuracy and the authors' signature problem-scenario approach clearly show how to apply statistical methods to practical business situations. New case problems and self-tests allow students to challenge their personal understanding. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.
Discover an accessible introduction to business statistics as ESSENTIALS OF MODERN BUSINESS STATISTICS, 7E balances a conceptual understanding of statistics with real-world applications of statistical methodology. The book integrates Microsoft Excel 2016, providing step-by-step instructions and screen captures to help readers master the latest Excel tools. Extremely reader-friendly, this edition includes numerous tools to maximize the user's success, including Self-Test Exercises, margin annotations, insightful Notes and Comments, and real-world Methods and Applications exercises. Eleven new Case Problems, as well as new Statistics in Practice applications and real data examples and exercises, give readers opportunities to put concepts into practice. Readers find everything needed to acquire key Excel 2016 skills and gain a strong understanding of business statistics. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.
Designed for a graduate course in applied statistics, Nonparametric Methods in Statistics with SAS Applications teaches students how to apply nonparametric techniques to statistical data. It starts with the tests of hypotheses and moves on to regression modeling, time-to-event analysis, density estimation, and resampling methods. The text begins with classical nonparametric hypotheses testing, including the sign, Wilcoxon sign-rank and rank-sum, Ansari-Bradley, Kolmogorov-Smirnov, Friedman rank, Kruskal-Wallis H, Spearman rank correlation coefficient, and Fisher exact tests. It then discusses smoothing techniques (loess and thin-plate splines) for classical nonparametric regression as well as binary logistic and Poisson models. The author also describes time-to-event nonparametric estimation methods, such as the Kaplan-Meier survival curve and Cox proportional hazards model, and presents histogram and kernel density estimation methods. The book concludes with the basics of jackknife and bootstrap interval estimation. Drawing on data sets from the author’s many consulting projects, this classroom-tested book includes various examples from psychology, education, clinical trials, and other areas. It also presents a set of exercises at the end of each chapter. All examples and exercises require the use of SAS 9.3 software. Complete SAS codes for all examples are given in the text. Large data sets for the exercises are available on the author’s website.
The subject of time series is of considerable interest, especially among researchers in econometrics, engineering, and the natural sciences. As part of the prestigious Wiley Series in Probability and Statistics, this book provides a lucid introduction to the field and, in this new Second Edition, covers the important advances of recent years, including nonstationary models, nonlinear estimation, multivariate models, state space representations, and empirical model identification. New sections have also been added on the Wold decomposition, partial autocorrelation, long memory processes, and the Kalman filter. Major topics include: * Moving average and autoregressive processes * Introduction to Fourier analysis * Spectral theory and filtering * Large sample theory * Estimation of the mean and autocorrelations * Estimation of the spectrum * Parameter estimation * Regression, trend, and seasonality * Unit root and explosive time series To accommodate a wide variety of readers, review material, especially on elementary results in Fourier analysis, large sample statistics, and difference equations, has been included.
Vital Statistics: an introduction to health science statistics e-book is a new Australian publication. This textbook draws on real world, health-related and local examples, with a broad appeal to the Health Sciences student. It demonstrates how an understanding of statistics is useful in the real world, as well as in statistics exams. Vital Statistics: an introduction to health science statistics e-book is a relatively easy-to-read book that will painlessly introduce or re-introduce you to the statistical basics before guiding you through more demanding statistical challenges. Written in recognition of Health Sciences courses which require knowledge of statistical literacy, this book guides the reader to an understanding of why, as well as how and when to use statistics. It explores: How data relates to information, and how information relates to knowledge How to use statistics to distinguish information from disinformation The importance of probability, in statistics and in life That inferential statistics allow us to infer from samples to populations, and how useful such inferences can be How to appropriately apply and interpret statistical measures of difference and association How qualitative and quantitative methods differ, and when it’s appropriate to use each The special statistical needs of the health sciences, and some especially health science relevant statistics The vital importance of computers in the statistical analysis of data, and gives an overview of the most commonly used analyses Real-life local examples of health statistics are presented, e.g. A study conducted at the Department of Obstetrics and Gynecology, University of Utah School of Medicine, explored whether there might be a systematic bias affecting the results of genetic specimen tests, which could affect their generalizability. Reader-friendly writing style t-tests/ ANOVA family of inferential statistics all use variants of the same basic formula Learning Objectives at the start of each chapter and Quick Reference Summaries at the end of each chapter provide the reader with a scope of the content within each chapter.
The fourth edition of the popular Handbook of Parametric and Nonparametric Statistical Procedures covers 160 of the most commonly used parametric and nonparametric statistical procedures encountered in theory and in practice. Featuring 26 new statistical tests and examples as well as 55 new figures, this edition provides new material on regression diagnostics, including the Durbin-Watson test. The book provides a new section on multivariate analysis with additional information on matrix algebra, uses of Hotellings T2, and multivariate analysis of variance and covariance. Sections on medical statistics, clinical trials, survival analysis, and analysis of censored data are also presented in this edition.
Written to convey an intuitive feel for both theory and practice, its main objective is to illustrate what a powerful tool density estimation can be when used not only with univariate and bivariate data but also in the higher dimensions of trivariate and quadrivariate information. Major concepts are presented in the context of a histogram in order to simplify the treatment of advanced estimators. Features 12 four-color plates, numerous graphic illustrations as well as a multitude of problems and solutions.