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Statistical Planning and Inference

Statistical Planning and Inference PDF Author: Subir Ghosh
Publisher: Wiley
ISBN: 9781119962786
Category : Science
Languages : en
Pages : 512

Book Description
This book introduces statistical planning and inference, presenting both classical theory and the major developments in the field. Each chapter presents problems and their solutions along with illustrative examples to introduce concepts and methods, and is supported by a supplementary website featuring guidance on how to implement methods using R.

Statistical Planning and Inference

Statistical Planning and Inference PDF Author: Subir Ghosh
Publisher: Wiley
ISBN: 9781119962786
Category : Science
Languages : en
Pages : 512

Book Description
This book introduces statistical planning and inference, presenting both classical theory and the major developments in the field. Each chapter presents problems and their solutions along with illustrative examples to introduce concepts and methods, and is supported by a supplementary website featuring guidance on how to implement methods using R.

Journal of Statistical Planning and Inference

Journal of Statistical Planning and Inference PDF Author: North-Holland Publishing Company
Publisher:
ISBN:
Category :
Languages : en
Pages : 812

Book Description


Statistical Inference in Stochastic Processes

Statistical Inference in Stochastic Processes PDF Author: Ishwar V. Basawa
Publisher:
ISBN:
Category :
Languages : en
Pages : 217

Book Description


Journal of Statistical Planning and Inference

Journal of Statistical Planning and Inference PDF Author:
Publisher:
ISBN:
Category : Mathematical statistics
Languages : en
Pages : 842

Book Description


Journal of statistical planning and inference

Journal of statistical planning and inference PDF Author: Elsevier Science (Firm)
Publisher:
ISBN:
Category :
Languages : en
Pages :

Book Description


Essentials of Statistical Inference Planning and Data Analysis

Essentials of Statistical Inference Planning and Data Analysis PDF Author: S. Ejaz Ahmed
Publisher:
ISBN: 9780176621018
Category : Mathematical statistics
Languages : en
Pages : 444

Book Description


Statistical Inference

Statistical Inference PDF Author: Michael J. Panik
Publisher: John Wiley & Sons
ISBN: 1118309804
Category : Mathematics
Languages : en
Pages : 294

Book Description
A concise, easily accessible introduction to descriptive and inferential techniques Statistical Inference: A Short Course offers a concise presentation of the essentials of basic statistics for readers seeking to acquire a working knowledge of statistical concepts, measures, and procedures. The author conducts tests on the assumption of randomness and normality, provides nonparametric methods when parametric approaches might not work. The book also explores how to determine a confidence interval for a population median while also providing coverage of ratio estimation, randomness, and causality. To ensure a thorough understanding of all key concepts, Statistical Inference provides numerous examples and solutions along with complete and precise answers to many fundamental questions, including: How do we determine that a given dataset is actually a random sample? With what level of precision and reliability can a population sample be estimated? How are probabilities determined and are they the same thing as odds? How can we predict the level of one variable from that of another? What is the strength of the relationship between two variables? The book is organized to present fundamental statistical concepts first, with later chapters exploring more advanced topics and additional statistical tests such as Distributional Hypotheses, Multinomial Chi-Square Statistics, and the Chi-Square Distribution. Each chapter includes appendices and exercises, allowing readers to test their comprehension of the presented material. Statistical Inference: A Short Course is an excellent book for courses on probability, mathematical statistics, and statistical inference at the upper-undergraduate and graduate levels. The book also serves as a valuable reference for researchers and practitioners who would like to develop further insights into essential statistical tools.

Introduction to Statistical Inference

Introduction to Statistical Inference PDF Author: E. S. Keeping
Publisher: Courier Corporation
ISBN: 9780486685021
Category : Mathematics
Languages : en
Pages : 484

Book Description
This excellent text emphasizes the inferential and decision-making aspects of statistics. The first chapter is mainly concerned with the elements of the calculus of probability. Additional chapters cover the general properties of distributions, testing hypotheses, and more.

Statistics '91 Canada Conference Papers

Statistics '91 Canada Conference Papers PDF Author: Canada. Statistics
Publisher:
ISBN:
Category :
Languages : en
Pages : 310

Book Description


Probabilistic Foundations of Statistical Network Analysis

Probabilistic Foundations of Statistical Network Analysis PDF Author: Harry Crane
Publisher: CRC Press
ISBN: 1351807323
Category : Business & Economics
Languages : en
Pages : 432

Book Description
Probabilistic Foundations of Statistical Network Analysis presents a fresh and insightful perspective on the fundamental tenets and major challenges of modern network analysis. Its lucid exposition provides necessary background for understanding the essential ideas behind exchangeable and dynamic network models, network sampling, and network statistics such as sparsity and power law, all of which play a central role in contemporary data science and machine learning applications. The book rewards readers with a clear and intuitive understanding of the subtle interplay between basic principles of statistical inference, empirical properties of network data, and technical concepts from probability theory. Its mathematically rigorous, yet non-technical, exposition makes the book accessible to professional data scientists, statisticians, and computer scientists as well as practitioners and researchers in substantive fields. Newcomers and non-quantitative researchers will find its conceptual approach invaluable for developing intuition about technical ideas from statistics and probability, while experts and graduate students will find the book a handy reference for a wide range of new topics, including edge exchangeability, relative exchangeability, graphon and graphex models, and graph-valued Levy process and rewiring models for dynamic networks. The author’s incisive commentary supplements these core concepts, challenging the reader to push beyond the current limitations of this emerging discipline. With an approachable exposition and more than 50 open research problems and exercises with solutions, this book is ideal for advanced undergraduate and graduate students interested in modern network analysis, data science, machine learning, and statistics. Harry Crane is Associate Professor and Co-Director of the Graduate Program in Statistics and Biostatistics and an Associate Member of the Graduate Faculty in Philosophy at Rutgers University. Professor Crane’s research interests cover a range of mathematical and applied topics in network science, probability theory, statistical inference, and mathematical logic. In addition to his technical work on edge and relational exchangeability, relative exchangeability, and graph-valued Markov processes, Prof. Crane’s methods have been applied to domain-specific cybersecurity and counterterrorism problems at the Foreign Policy Research Institute and RAND’s Project AIR FORCE.