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A Primer on Statistical Distributions

A Primer on Statistical Distributions PDF Author: Narayanaswamy Balakrishnan
Publisher: John Wiley & Sons
ISBN: 0471722219
Category : Mathematics
Languages : en
Pages : 322

Book Description
Designed as an introduction to statistical distribution theory. * Includes a first chapter on basic notations and definitions that are essential to working with distributions. * Remaining chapters are divided into three parts: Discrete Distributions, Continuous Distributions, and Multivariate Distributions. * Exercises are incorporated throughout the text in order to enhance understanding of materials just taught.

A Primer on Statistical Distributions

A Primer on Statistical Distributions PDF Author: Narayanaswamy Balakrishnan
Publisher: John Wiley & Sons
ISBN: 0471722219
Category : Mathematics
Languages : en
Pages : 322

Book Description
Designed as an introduction to statistical distribution theory. * Includes a first chapter on basic notations and definitions that are essential to working with distributions. * Remaining chapters are divided into three parts: Discrete Distributions, Continuous Distributions, and Multivariate Distributions. * Exercises are incorporated throughout the text in order to enhance understanding of materials just taught.

Statistical Distributions

Statistical Distributions PDF Author: Catherine Forbes
Publisher: John Wiley & Sons
ISBN: 1118097823
Category : Mathematics
Languages : en
Pages : 206

Book Description
A new edition of the trusted guide on commonly used statistical distributions Fully updated to reflect the latest developments on the topic, Statistical Distributions, Fourth Edition continues to serve as an authoritative guide on the application of statistical methods to research across various disciplines. The book provides a concise presentation of popular statistical distributions along with the necessary knowledge for their successful use in data modeling and analysis. Following a basic introduction, forty popular distributions are outlined in individual chapters that are complete with related facts and formulas. Reflecting the latest changes and trends in statistical distribution theory, the Fourth Edition features: A new chapter on queuing formulas that discusses standard formulas that often arise from simple queuing systems Methods for extending independent modeling schemes to the dependent case, covering techniques for generating complex distributions from simple distributions New coverage of conditional probability, including conditional expectations and joint and marginal distributions Commonly used tables associated with the normal (Gaussian), student-t, F and chi-square distributions Additional reviewing methods for the estimation of unknown parameters, such as the method of percentiles, the method of moments, maximum likelihood inference, and Bayesian inference Statistical Distributions, Fourth Edition is an excellent supplement for upper-undergraduate and graduate level courses on the topic. It is also a valuable reference for researchers and practitioners in the fields of engineering, economics, operations research, and the social sciences who conduct statistical analyses.

A Mathematical Primer for Social Statistics

A Mathematical Primer for Social Statistics PDF Author: John Fox
Publisher: SAGE Publications
ISBN: 1071833243
Category : Social Science
Languages : en
Pages : 199

Book Description
A Mathematical Primer for Social Statistics, Second Edition presents mathematics central to learning and understanding statistical methods beyond the introductory level: the basic "language" of matrices and linear algebra and its visual representation, vector geometry; differential and integral calculus; probability theory; common probability distributions; statistical estimation and inference, including likelihood-based and Bayesian methods. The volume concludes by applying mathematical concepts and operations to a familiar case, linear least-squares regression. The Second Edition pays more attention to visualization, including the elliptical geometry of quadratic forms and its application to statistics. It also covers some new topics, such as an introduction to Markov-Chain Monte Carlo methods, which are important in modern Bayesian statistics. A companion website includes materials that enable readers to use the R statistical computing environment to reproduce and explore computations and visualizations presented in the text. The book is an excellent companion to a "math camp" or a course designed to provide foundational mathematics needed to understand relatively advanced statistical methods.

A Mathematical Primer for Social Statistics

A Mathematical Primer for Social Statistics PDF Author: John Fox
Publisher: SAGE
ISBN: 1412960800
Category : Social Science
Languages : en
Pages : 185

Book Description
The ideal primer for students and researchers across the social sciences who wish to master the necessary maths in order to pursue studies involving advanced statistical methods

Handbook of Statistical Distributions with Applications

Handbook of Statistical Distributions with Applications PDF Author: K. Krishnamoorthy
Publisher: CRC Press
ISBN: 1420011375
Category : Mathematics
Languages : en
Pages : 371

Book Description
In the area of applied statistics, scientists use statistical distributions to model a wide range of practical problems, from modeling the size grade distribution of onions to modeling global positioning data. To apply these probability models successfully, practitioners and researchers must have a thorough understanding of the theory as well as a

A Primer in Probability, Second Edition

A Primer in Probability, Second Edition PDF Author: Kathleen Subrahmaniam
Publisher: CRC Press
ISBN: 9780849306617
Category : Mathematics
Languages : en
Pages : 338

Book Description
Somewhat revised/expanded new edition of a problem-oriented introductory undergraduate text, the first edition of which appeared about a decade ago. The author writes with courteous clarity, and imposes only modest demands upon the mathematical skills of her readers. Problems at the end of each of t

Primer for Data Analytics and Graduate Study in Statistics

Primer for Data Analytics and Graduate Study in Statistics PDF Author: Douglas Wolfe
Publisher: Springer Nature
ISBN: 3030474798
Category : Mathematics
Languages : en
Pages : 233

Book Description
This book is specially designed to refresh and elevate the level of understanding of the foundational background in probability and distributional theory required to be successful in a graduate-level statistics program. Advanced undergraduate students and introductory graduate students from a variety of quantitative backgrounds will benefit from the transitional bridge that this volume offers, from a more generalized study of undergraduate mathematics and statistics to the career-focused, applied education at the graduate level. In particular, it focuses on growing fields that will be of potential interest to future M.S. and Ph.D. students, as well as advanced undergraduates heading directly into the workplace: data analytics, statistics and biostatistics, and related areas.

A Statistics Primer for Managers

A Statistics Primer for Managers PDF Author: John J. Clark
Publisher: MacMillan Publishing Company
ISBN:
Category : Management
Languages : en
Pages : 280

Book Description
Explains the fundamentals of statistics and describes techniques for interpreting statistical data and making decisions based on statistical reports.

Primer of Statistics

Primer of Statistics PDF Author: Sir William Palin Elderton
Publisher:
ISBN:
Category : Mathematical statistics
Languages : en
Pages : 110

Book Description


Causal Inference in Statistics

Causal Inference in Statistics PDF Author: Judea Pearl
Publisher: John Wiley & Sons
ISBN: 1119186862
Category : Mathematics
Languages : en
Pages : 162

Book Description
CAUSAL INFERENCE IN STATISTICS A Primer Causality is central to the understanding and use of data. Without an understanding of cause–effect relationships, we cannot use data to answer questions as basic as "Does this treatment harm or help patients?" But though hundreds of introductory texts are available on statistical methods of data analysis, until now, no beginner-level book has been written about the exploding arsenal of methods that can tease causal information from data. Causal Inference in Statistics fills that gap. Using simple examples and plain language, the book lays out how to define causal parameters; the assumptions necessary to estimate causal parameters in a variety of situations; how to express those assumptions mathematically; whether those assumptions have testable implications; how to predict the effects of interventions; and how to reason counterfactually. These are the foundational tools that any student of statistics needs to acquire in order to use statistical methods to answer causal questions of interest. This book is accessible to anyone with an interest in interpreting data, from undergraduates, professors, researchers, or to the interested layperson. Examples are drawn from a wide variety of fields, including medicine, public policy, and law; a brief introduction to probability and statistics is provided for the uninitiated; and each chapter comes with study questions to reinforce the readers understanding.