Search results for: statistical-inference-for-everyone

Statistical Inference For Everyone

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Statistical Inference for Everyone

Author : Brian Blais
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Approaching an introductory statistical inference textbook in a novel way, this book is motivated by the perspective of "probability theory as logic". Targeted to the typical "Statistics 101" college student this book covers the topics typically treated in such a course - but from a fresh angle. This book walks through a simple introduction to probability, and then applies those principles to all problems of inference. Topics include hypothesis testing, data visualization, parameter inference, and model comparison. Statistical Inference for Everyone is freely available under the Creative Commons License, and includes a software library in Python for making calculations and visualizations straightforward.

All of Statistics

Author : Larry Wasserman
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This book surveys a broad range of topics in probability and mathematical statistics. It provides the statistical background that a computer scientist needs to work in the area of machine learning.

Computer Age Statistical Inference

Author : Bradley Efron
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Take an exhilarating journey through the modern revolution in statistics with two of the ringleaders.

The Logical Foundations of Statistical Inference

Author : Henry E. Kyburg Jr.
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Everyone knows it is easy to lie with statistics. It is important then to be able to tell a statistical lie from a valid statistical inference. It is a relatively widely accepted commonplace that our scientific knowledge is not certain and incorrigible, but merely probable, subject to refinement, modifi cation, and even overthrow. The rankest beginner at a gambling table understands that his decisions must be based on mathematical ex pectations - that is, on utilities weighted by probabilities. It is widely held that the same principles apply almost all the time in the game of life. If we turn to philosophers, or to mathematical statisticians, or to probability theorists for criteria of validity in statistical inference, for the general principles that distinguish well grounded from ill grounded generalizations and laws, or for the interpretation of that probability we must, like the gambler, take as our guide in life, we find disagreement, confusion, and frustration. We might be prepared to find disagreements on a philosophical and theoretical level (although we do not find them in the case of deductive logic) but we do not expect, and we may be surprised to find, that these theoretical disagreements lead to differences in the conclusions that are regarded as 'acceptable' in the practice of science and public affairs, and in the conduct of business.

Statistical Inference

Author : Michael J. Panik
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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.

Statistical Inference

Author : George Casella
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This book builds theoretical statistics from the first principles of probability theory. Starting from the basics of probability, the authors develop the theory of statistical inference using techniques, definitions, and concepts that are statistical and are natural extensions and consequences of previous concepts. Intended for first-year graduate students, this book can be used for students majoring in statistics who have a solid mathematics background. It can also be used in a way that stresses the more practical uses of statistical theory, being more concerned with understanding basic statistical concepts and deriving reasonable statistical procedures for a variety of situations, and less concerned with formal optimality investigations. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.

Introduction to Linear Models and Statistical Inference

Author : Steven J. Janke
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A multidisciplinary approach that emphasizes learning by analyzingreal-world data sets This book is the result of the authors' hands-on classroomexperience and is tailored to reflect how students best learn toanalyze linear relationships. The text begins with the introductionof four simple examples of actual data sets. These examples aredeveloped and analyzed throughout the text, and more complicatedexamples of data sets are introduced along the way. Taking amultidisciplinary approach, the book traces the conclusion of theanalyses of data sets taken from geology, biology, economics,psychology, education, sociology, and environmental science. As students learn to analyze the data sets, they masterincreasingly sophisticated linear modeling techniques,including: * Simple linear models * Multivariate models * Model building * Analysis of variance (ANOVA) * Analysis of covariance (ANCOVA) * Logistic regression * Total least squares The basics of statistical analysis are developed and emphasized,particularly in testing the assumptions and drawing inferences fromlinear models. Exercises are included at the end of each chapter totest students' skills before moving on to more advanced techniquesand models. These exercises are marked to indicate whethercalculus, linear algebra, or computer skills are needed. Unlike other texts in the field, the mathematics underlying themodels is carefully explained and accessible to students who maynot have any background in calculus or linear algebra. Mostchapters include an optional final section on linear algebra forstudents interested in developing a deeper understanding. The many data sets that appear in the text are available on thebook's Web site. The MINITAB(r) software program is used toillustrate many of the examples. For students unfamiliar withMINITAB(r), an appendix introduces the key features needed to studylinear models. With its multidisciplinary approach and use of real-world data setsthat bring the subject alive, this is an excellent introduction tolinear models for students in any of the natural or socialsciences.

Statistical Inference and Probability

Author : John MacInnes
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Part of The SAGE Quantitative Research Kit, this concise text breaks down the complex topic of inferential statistics with accessible language and detailed examples. Covering a range of topics, it provides you with the know-how and confidence needed for a successful quantitative research journey.

Foundations of Probability Theory Statistical Inference and Statistical Theories of Science

Author : W.L. Harper
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In May of 1973 we organized an international research colloquium on foundations of probability, statistics, and statistical theories of science at the University of Western Ontario. During the past four decades there have been striking formal advances in our understanding of logic, semantics and algebraic structure in probabilistic and statistical theories. These advances, which include the development of the relations between semantics and metamathematics, between logics and algebras and the algebraic-geometrical foundations of statistical theories (especially in the sciences), have led to striking new insights into the formal and conceptual structure of probability and statistical theory and their scientific applications in the form of scientific theory. The foundations of statistics are in a state of profound conflict. Fisher's objections to some aspects of Neyman-Pearson statistics have long been well known. More recently the emergence of Bayesian statistics as a radical alternative to standard views has made the conflict especially acute. In recent years the response of many practising statisticians to the conflict has been an eclectic approach to statistical inference. Many good statisticians have developed a kind of wisdom which enables them to know which problems are most appropriately handled by each of the methods available. The search for principles which would explain why each of the methods works where it does and fails where it does offers a fruitful approach to the controversy over foundations.

Linguistic Evidence Statistical Inference and Disputed Authorship

Author : Robert Stanley Wachal
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An Introduction to Statistical Methods and Data Analysis

Author : Lyman Ott
File Size : 38.19 MB
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Introduction to business statistics

Author : Alan H. Kvanli
File Size : 73.88 MB
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Mathematics for Management Series Statistical inference

Author : Clifford Harry Springer
File Size : 89.95 MB
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The Frontiers of Modern Statistical Inference Procedures II

Author : Eve Bofinger
File Size : 23.62 MB
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Proceedings of the Business and Economic Statistics Section

Author : American Statistical Association. Business and Economic Statistics Section
File Size : 49.86 MB
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Statistical Inference

Author : Eugene S. Edgington
File Size : 75.10 MB
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The Application of Quantitative Methods in Archaeology

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Lectures in the Theory of Statistical Inference

Author : Michael Capobianco
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Proceedings of the Summer Research Institute on Statistical Inference for Stochastic Processes Bloomington Indiana July 31 August 9 1974 Statistical inference and related topics

Author : Madan Lal Puri
File Size : 38.42 MB
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