Books in Statistics

Handbook of Statistical Analysis and Data Mining Applications

2nd Edition
November 9, 2017
Ken Yale + 2 more
English
eBook
9 7 8 0 1 2 4 1 6 6 4 5 5

Handbook of Statistical Analysis and Data Mining Applications, Second Edition, is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers, both academic and industrial, through all stages of data analysis, model building and implementation. The handbook helps users discern technical and business problems, understand the strengths and weaknesses of modern data mining algorithms and employ the right statistical methods for practical application. This book is an ideal reference for users who want to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. It has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques and discusses their application to real problems in ways accessible and beneficial to practitioners across several areas—from science and engineering, to medicine, academia and commerce.

Disease Modelling and Public Health, Part B

1st Edition
Volume 37
October 31, 2017
Arni S.R. Srinivasa Rao + 2 more
English
Hardback
9 7 8 0 4 4 4 6 3 9 7 5 2
eBook
9 7 8 0 4 4 4 6 3 9 7 6 9

Handbook of Statistics: Disease Modelling and Public Health, Part B, Volume 37 addresses new challenges in existing and emerging diseases. As a two part volume, this title covers an extensive range of techniques in the field, with this book including chapters on Reaction diffusion equations and their application on bacterial communication, Spike and slab methods in disease modeling, Mathematical modeling of mass screening and parameter estimation, Individual-based and agent-based models for infectious disease transmission and evolution: an overview, and a section on Visual Clustering of Static and Dynamic High Dimensional Data. This volume covers the lack of availability of complete data relating to disease symptoms and disease epidemiology, one of the biggest challenges facing vaccine developers, public health planners, epidemiologists and health sector researchers.

Disease Modelling and Public Health, Part A

1st Edition
Volume 36
October 13, 2017
Arni S.R. Srinivasa Rao + 2 more
English
Hardback
9 7 8 0 4 4 4 6 3 9 6 8 4
eBook
9 7 8 0 4 4 4 6 3 9 6 9 1

Disease Modelling and Public Health, Part A, Volume 36 addresses new challenges in existing and emerging diseases with a variety of comprehensive chapters that cover Infectious Disease Modeling, Bayesian Disease Mapping for Public Health, Real time estimation of the case fatality ratio and risk factor of death, Alternative Sampling Designs for Time-To-Event Data with Applications to Biomarker Discovery in Alzheimer's Disease, Dynamic risk prediction for cardiovascular disease: An illustration using the ARIC Study, Theoretical advances in type 2 diabetes, Finite Mixture Models in Biostatistics, and Models of Individual and Collective Behavior for Public Health Epidemiology. As a two part volume, the series covers an extensive range of techniques in the field. It present a vital resource for statisticians who need to access a number of different methods for assessing epidemic spread in population, or in formulating public health policy.

Biostatistics and Computer-based Analysis of Health Data Using SAS

1st Edition
June 22, 2017
Christophe Lalanne + 1 more
English
Hardback
9 7 8 1 7 8 5 4 8 1 1 1 6
eBook
9 7 8 0 0 8 1 0 1 1 7 1 3

This volume of the Biostatistics and Health Sciences Set focuses on statistics applied to clinical research.The use of SAS for data management and statistical modeling is illustrated using various examples. Many aspects of data processing and statistical analysis of cross-sectional and experimental medical data are covered, including regression models commonly found in medical statistics. This practical book is primarily intended for health researchers with a basic knowledge of statistical methodology. Assuming basic concepts, the authors focus on the practice of biostatistical methods essential to clinical research, epidemiology and analysis of biomedical data (including comparison of two groups, analysis of categorical data, ANOVA, linear and logistic regression, and survival analysis). The use of examples from clinical trials and epidemiological studies provide the basis for a series of practical exercises, which provide instruction and familiarize the reader with essential SAS commands.

Inequalities and Extremal Problems in Probability and Statistics

1st Edition
May 8, 2017
Iosif Pinelis + 4 more
English
Paperback
9 7 8 0 1 2 8 0 9 8 1 8 9
eBook
9 7 8 0 1 2 8 0 9 8 9 2 9

Inequalities and Extremal Problems in Probability and Statistics: Selected Topics presents various kinds of useful inequalities that are applicable in many areas of mathematics, the sciences, and engineering. The book enables the reader to grasp the importance of inequalities and how they relate to probability and statistics. This will be an extremely useful book for researchers and graduate students in probability, statistics, and econometrics, as well as specialists working across sciences, engineering, financial mathematics, insurance, and mathematical modeling of large risks.

Optimal Sports Math, Statistics, and Fantasy

1st Edition
April 6, 2017
Robert Kissell + 1 more
English
Hardback
9 7 8 0 1 2 8 0 5 1 6 3 4
eBook
9 7 8 0 1 2 8 0 5 2 9 3 8

Optimal Sports Math, Statistics, and Fantasy provides the sports community—students, professionals, and casual sports fans—with the essential mathematics and statistics required to objectively analyze sports teams, evaluate player performance, and predict game outcomes. These techniques can also be applied to fantasy sports competitions. Readers will learn how to: Accurately rank sports teams Compute winning probability Calculate expected victory margin Determine the set of factors that are most predictive of team and player performance Optimal Sports Math, Statistics, and Fantasy also illustrates modeling techniques that can be used to decode and demystify the mysterious computer ranking schemes that are often employed by post-season tournament selection committees in college and professional sports. These methods offer readers a verifiable and unbiased approach to evaluate and rank teams, and the proper statistical procedures to test and evaluate the accuracy of different models. Optimal Sports Math, Statistics, and Fantasy delivers a proven best-in-class quantitative modeling framework with numerous applications throughout the sports world.

Introductory Statistics

4th Edition
January 26, 2017
Sheldon M. Ross
English
Hardback
9 7 8 0 1 2 8 0 4 3 1 7 2
eBook
9 7 8 0 1 2 8 0 4 3 6 1 5

Introductory Statistics, Fourth Edition, reviews statistical concepts and techniques in a manner that will teach students not only how and when to utilize the statistical procedures developed, but also how to understand why these procedures should be used. The text's main merits are the clarity of presentation, contemporary examples and applications from diverse areas, an explanation of intuition, and the ideas behind the statistical methods. Concepts are motivated, illustrated, and explained in a way that attempts to increase one's intuition. To quote from the preface, it is only when a student develops a feel or intuition for statistics that she or he is really on the path toward making sense of data. Ross achieves this goal through a coherent mix of mathematical analysis, intuitive discussions, and examples. Applications and examples refer to real-world issues, such as gun control, stock price models, health issues, driving age limits, school admission ages, use of helmets, sports, scientific fraud, and many others. Examples relating to data mining techniques using the number of Google queries or Twitter tweets are also considered. For this fourth edition, new topical coverage includes sections on Pareto distribution and the 80-20 rule, Benford's law, added material on odds and joint distributions and correlation, logistic regression, A-B testing, and more modern (big data) examples and exercises.

Analysis for Time-to-Event Data under Censoring and Truncation

1st Edition
September 26, 2016
Hongsheng Dai + 1 more
English
Paperback
9 7 8 0 1 2 8 0 5 4 8 0 2
eBook
9 7 8 0 0 8 1 0 1 0 0 8 2

Survival Analysis for Bivariate Truncated Data provides readers with a comprehensive review on the existing works on survival analysis for truncated data, mainly focusing on the estimation of univariate and bivariate survival function. The most distinguishing feature of survival data is known as censoring, which occurs when the survival time can only be exactly observed within certain time intervals. A second feature is truncation, which is often deliberate and usually due to selection bias in the study design. Truncation presents itself in different ways. For example, left truncation, which is often due to a so-called late entry bias, occurs when individuals enter a study at a certain age and are followed from this delayed entry time. Right truncation arises when only individuals who experienced the event of interest before a certain time point can be observed. Analyzing truncated survival data without considering the potential selection bias may lead to seriously biased estimates of the time to event of interest and the impact of risk factors.

Introduction to Robust Estimation and Hypothesis Testing

4th Edition
September 2, 2016
Rand R. Wilcox
English
eBook
9 7 8 0 1 2 8 0 4 7 8 1 1

Introduction to Robust Estimating and Hypothesis Testing, 4th Editon, is a ‘how-to’ on the application of robust methods using available software. Modern robust methods provide improved techniques for dealing with outliers, skewed distribution curvature and heteroscedasticity that can provide substantial gains in power as well as a deeper, more accurate and more nuanced understanding of data. Since the last edition, there have been numerous advances and improvements. They include new techniques for comparing groups and measuring effect size as well as new methods for comparing quantiles. Many new regression methods have been added that include both parametric and nonparametric techniques. The methods related to ANCOVA have been expanded considerably. New perspectives related to discrete distributions with a relatively small sample space are described as well as new results relevant to the shift function. The practical importance of these methods is illustrated using data from real world studies. The R package written for this book now contains over 1200 functions. New to this edition 35% revised content Covers many new and improved R functions New techniques that deal with a wide range of situations

Biostatistics and Computer-based Analysis of Health Data using Stata

1st Edition
August 24, 2016
Christophe Lalanne + 1 more
English
Hardback
9 7 8 1 7 8 5 4 8 1 4 2 0
eBook
9 7 8 0 0 8 1 0 1 0 8 4 6

This volume of the Biostatistics and Health Sciences Set focuses on statistics applied to clinical research. The use of Stata for data management and statistical modeling is illustrated using various examples. Many aspects of data processing and statistical analysis of cross-sectional and experimental medical data are covered, including regression models commonly found in medical statistics. This practical book is primarily intended for health researchers with basic knowledge of statistical methodology. Assuming basic concepts, the authors focus on the practice of biostatistical methods essential to clinical research, epidemiology and analysis of biomedical data (including comparison of two groups, analysis of categorical data, ANOVA, linear and logistic regression, and survival analysis). The use of examples from clinical trials and epideomological studies provide the basis for a series of practical exercises, which provide instruction and familiarize the reader with essential Stata packages and commands.

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