Illuminating Statistical Analysis Using Scenarios and Simulations - Jeffrey E. Kottemann

Книга "Illuminating Statistical Analysis Using Scenarios and Simulations" представляет собой интегрированный подход к статистическим сценариям и симуляциям, который помогает читателям развивать ключевые интуиции, необходимые для понимания широкого спектра концепций и методов статистики и выводов. Автор использует механизмы сценариев и симуляций для объяснения основных концепций статистики и статистического вывода. Симуляции, основанные на конкретных сценариях, позволяют получить результаты, которые можно было бы получить, если бы большое количество людей исследовали тот же самый сценарий, каждый со своими доказательствами. Графические изображения результатов симуляций предоставляют прямой и интуитивный подход к методам статистического вывода. Этот подход легко связывается с традиционными формулами и объясняется на примерах различных статистических явлений. В книге также рассматриваются такие темы, как байесовская статистика, добыча данных, перекрестная проверка модели, робастная регрессия и повторное выборочное исследование. Книга содержит множество примеров задач в каждой главе с подробными решениями, а также приложение, которое служит руководством для быстрого и легкого создания симуляций с помощью Microsoft® Office Excel®. "Illuminating Statistical Analysis Using Scenarios and Simulations" является идеальным учебным пособием для курсов, семинаров и мастер-классов по статистике и статистическому выводу, а также подходит для самостоятельного изучения. Книга также может быть полезна исследователям, ученым, менеджерам, техникам и другим людям, заинтересованным в статистическом анализе. Автор книги - Джеффри Э. Коттеманн, профессор в Пердью-школе Университета Солсбери.

This book blends statistical concepts with simulations in an approach designed to help readers grasp key intuitions behind a wide range of topics in statistics, including those that are more advanced. Taking the Core Topics such as Bernoulli Trials, Sampling Distributions, Variance, Hypothesis Testing, ANOVA, Regression, Correlation, Bayesian Methods, Data Mining and more, it features a mix of explanation and simulation, depicting the simulated results of scenarios instead of just a fast narrative explaining why this or that method works how it does without illustrating its influences, Kottemann integrates similarity or difference, randomness or bias into the description and application of various approaches to statistical inference, thereby stressing the uncertainty inherent in any statistical model, whether simple or complex. Sample simulation simulations allows readers to experience the impact that sample size, the degree of variability in observations, and probability of encountering an event actually have on deriving conclusions about unknown parameters, as well as develop an understanding for how one can incorporate and check assumptions about the quality of data estimates and their errors in creating whatever sort of inferences they desire. The examples used in this book also ensure relevance, utility, and applicability to real-world issues, so that statistical knowledge becomes less abstract and more usable.

Эта книга знакомит читателя с интегрированным подходом к статистическим сценариям и симуляциям, помогая вам развить базовые интуитивные способности для понимания широкого спектра понятий и методов статистики и выводов. Illuminating Statistical Methods, Using Scenarios, and Simulation освещает основные концепции статистики и статистического вывода с помощью двух механизмов: сценариев и симуляций.

Электронная Книга «Illuminating Statistical Analysis Using Scenarios and Simulations» написана автором Jeffrey E. Kottemann в году.

Минимальный возраст читателя: 0

Язык: Английский

ISBN: 9781119296348

Features an integrated approach of statistical scenarios and simulations to aid readers in developing key intuitions needed to understand the wide ranging concepts and methods of statistics and inference Illuminating Statistical Analysis Using Scenarios and Simulations presents the basic concepts of statistics and statistical inference using the dual mechanisms of scenarios and simulations. This approach helps readers develop key intuitions and deep understandings of statistical analysis. Scenario-specific sampling simulations depict the results that would be obtained by a very large number of individuals investigating the same scenario, each with their own evidence, while graphical depictions of the simulation results present clear and direct pathways to intuitive methods for statistical inference. These intuitive methods can then be easily linked to traditional formulaic methods, and the author does not simply explain the linkages, but rather provides demonstrations throughout for a broad range of statistical phenomena. In addition, induction and deduction are repeatedly interwoven, which fosters a natural «need to know basis» for ordering the topic coverage. Examining computer simulation results is central to the discussion and provides an illustrative way to (re)discover the properties of sample statistics, the role of chance, and to (re)invent corresponding principles of statistical inference. In addition, the simulation results foreshadow the various mathematical formulas that underlie statistical analysis. In addition, this book: • Features both an intuitive and analytical perspective and includes a broad introduction to the use of Monte Carlo simulation and formulaic methods for statistical analysis • Presents straight-forward coverage of the essentials of basic statistics and ensures proper understanding of key concepts such as sampling distributions, the effects of sample size and variance on uncertainty, analysis of proportion, mean and rank differences, covariance, correlation, and regression • Introduces advanced topics such as Bayesian statistics, data mining, model cross-validation, robust regression, and resampling • Contains numerous example problems in each chapter with detailed solutions as well as an appendix that serves as a manual for constructing simulations quickly and easily using Microsoft® Office Excel® Illuminating Statistical Analysis Using Scenarios and Simulations is an ideal textbook for courses, seminars, and workshops in statistics and statistical inference and is appropriate for self-study as well. The book also serves as a thought-provoking treatise for researchers, scientists, managers, technicians, and others with a keen interest in statistical analysis. Jeffrey E. Kottemann, Ph.D., is Professor in the Perdue School at Salisbury University. Dr. Kottemann has published articles in a wide variety of academic research journals in the fields of business administration, computer science, decision sciences, economics, engineering, information systems, psychology, and public administration. He received his Ph.D. in Systems and Quantitative Methods from the University of Arizona.