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Statistics of Financial Markets: Exercises and Solutions
by Wolfgang Karl Härdle Brenda López-Cabrera Szymon BorakPractice makes perfect. Therefore the best method of mastering models is working with them. This book contains a large collection of exercises and solutions which will help explain the statistics of financial markets. These practical examples are carefully presented and provide computational solutions to specific problems, all of which are calculated using R and Matlab. This study additionally looks at the concept of corresponding Quantlets, the name given to these program codes and which follow the name scheme SFSxyz123. The book is divided into three main parts, in which option pricing, time series analysis and advanced quantitative statistical techniques in finance is thoroughly discussed. The authors have overall successfully created the ideal balance between theoretical presentation and practical challenges.
Statistics of Medical Imaging (Chapman & Hall/CRC Interdisciplinary Statistics)
by Tianhu LeiStatistical investigation into technology not only provides a better understanding of the intrinsic features of the technology (analysis), but also leads to an improved design of the technology (synthesis). Physical principles and mathematical procedures of medical imaging technologies have been extensively studied during past decades. However, les
Statistics of the Galaxy Distribution
by Vicent J. Martinez Enn SaarOver the last decade, statisticians have developed new statistical tools in the field of spatial point processes. At the same time, observational efforts have yielded a huge amount of new cosmological data to analyze. Although the main tools in astronomy for comparing theoretical results with observation are statistical, in recent years, cosmologis
Statistics on the Table: The History of Statistical Concepts and Methods
by Stephen M. StiglerThis lively collection of essays examines in witty detail the history of some of the concepts involved in bringing statistical argument "to the table," and some of the pitfalls that have been encountered. The topics range from seventeenth-century medicine and the circulation of blood, to the cause of the Great Depression and the effect of the California gold discoveries of 1848 upon price levels, to the determinations of the shape of the Earth and the speed of light, to the meter of Virgil's poetry and the prediction of the Second Coming of Christ. The title essay tells how the statistician Karl Pearson came to issue the challenge to put "statistics on the table" to the economists Marshall, Keynes, and Pigou in 1911. The 1911 dispute involved the effect of parental alcoholism upon children, but the challenge is general and timeless: important arguments require evidence, and quantitative evidence requires statistical evaluation. Some essays examine deep and subtle statistical ideas such as the aggregation and regression paradoxes; others tell of the origin of the Average Man and the evaluation of fingerprints as a forerunner of the use of DNA in forensic science. Several of the essays are entirely nontechnical; all examine statistical ideas with an ironic eye for their essence and what their history can tell us about current disputes.
Statistics with Applications in Biology and Geology
by Preben Blaesild Jorgen GranfeldtThe use of statistics is fundamental to many endeavors in biology and geology. For students and professionals in these fields, there is no better way to build a statistical background than to present the concepts and techniques in a context relevant to their interests. Statistics with Applications in Biology and Geology provides a practical introduction to using fundamental parametric statistical models frequently applied to data analysis in biology and geology.Based on material developed for an introductory statistics course and classroom tested for nearly 10 years, this treatment establishes a firm basis in models, the likelihood method, and numeracy. The models addressed include one sample, two samples, one- and two-way analysis of variance, and linear regression for normal data and similar models for binomial, multinomial, and Poisson data. Building on the familiarity developed with those models, the generalized linear models are introduced, making it possible for readers to handle fairly complicated models for both continuous and discrete data. Models for directional data are treated as well. The emphasis is on parametric models, but the book also includes a chapter on the most important nonparametric tests.This presentation incorporates the use of the SAS statistical software package, which authors use to illustrate all of the statistical tools described. However, to reinforce understanding of the basic concepts, calculations for the simplest models are also worked through by hand. SAS programs and the data used in the examples and exercises are available on the Internet.
Statistics with Confidence: Confidence Intervals and Statistical Guidelines
by David Machin Douglas G Altman Trevor N Bryant Martin J GardnerThis highly popular introduction to confidence intervals has been thoroughly updated and expanded. It includes methods for using confidence intervals, with illustrative worked examples and extensive guidelines and checklists to help the novice.
Statistics with JMP
by Peter Goos David MeintrupPeter Goos, Department of Statistics, University ofLeuven, Faculty of Bio-Science Engineering and University ofAntwerp, Faculty of Applied Economics, BelgiumDavid Meintrup, Department of Mathematics and Statistics,University of Applied Sciences Ingolstadt, Faculty of MechanicalEngineering, GermanyThorough presentation of introductory statistics and probabilitytheory, with numerous examples and applications using JMPDescriptive Statistics and Probability provides anaccessible and thorough overview of the most important descriptivestatistics for nominal, ordinal and quantitative data withparticular attention to graphical representations. The authorsdistinguish their approach from many modern textbooks ondescriptive statistics and probability theory by offering acombination of theoretical and mathematical depth, and clear anddetailed explanations of concepts. Throughout the book, theuser-friendly, interactive statistical software package JMP is usedfor calculations, the computation of probabilities and the creationof figures. The examples are explained in detail, and accompaniedby step-by-step instructions and screenshots. The reader willtherefore develop an understanding of both the statistical theoryand its applications.Traditional graphs such as needle charts, histograms and pie chartsare included, as well as the more modern mosaic plots, bubble plotsand heat maps. The authors discuss probability theory, particularlydiscrete probability distributions and continuous probabilitydensities, including the binomial and Poisson distributions, andthe exponential, normal and lognormal densities. They use numerousexamples throughout to illustrate these distributions anddensities.Key features:Introduces each concept with practical examples anddemonstrations in JMP.Provides the statistical theory including detailed mathematicalderivations.Presents illustrative examples in each chapter accompanied bystep-by-step instructions and screenshots to help develop thereader's understanding of both the statistical theory and itsapplications.A supporting website with data sets and other teachingmaterials.This book is equally aimed at students in engineering, economicsand natural sciences who take classes in statistics as well as atmasters/advanced students in applied statistics and probabilitytheory. For teachers of applied statistics, this book provides arich resource of course material, examples and applications.
Statistics with JMP: Hypothesis Tests, Anova And Regression
by Peter Goos David MeintrupStatistics with JMP: Hypothesis Tests, ANOVA and Regression Peter Goos, University of Leuven and University of Antwerp, Belgium David Meintrup, University of Applied Sciences Ingolstadt, Germany A first course on basic statistical methodology using JMP This book provides a first course on parameter estimation (point estimates and confidence interval estimates), hypothesis testing, ANOVA and simple linear regression. The authors approach combines mathematical depth with numerous examples and demonstrations using the JMP software. Key features: Provides a comprehensive and rigorous presentation of introductory statistics that has been extensively classroom tested. Pays attention to the usual parametric hypothesis tests as well as to non-parametric tests (including the calculation of exact p-values). Discusses the power of various statistical tests, along with examples in JMP to enable in-sight into this difficult topic. Promotes the use of graphs and confidence intervals in addition to p-values. Course materials and tutorials for teaching are available on the book's companion website. Masters and advanced students in applied statistics, industrial engineering, business engineering, civil engineering and bio-science engineering will find this book beneficial. It also provides a useful resource for teachers of statistics particularly in the area of engineering.
Statistics with Julia: Fundamentals for Data Science, Machine Learning and Artificial Intelligence (Springer Series in the Data Sciences)
by Yoni Nazarathy Hayden KlokThis monograph uses the Julia language to guide the reader through an exploration of the fundamental concepts of probability and statistics, all with a view of mastering machine learning, data science, and artificial intelligence. The text does not require any prior statistical knowledge and only assumes a basic understanding of programming and mathematical notation. It is accessible to practitioners and researchers in data science, machine learning, bio-statistics, finance, or engineering who may wish to solidify their knowledge of probability and statistics. The book progresses through ten independent chapters starting with an introduction of Julia, and moving through basic probability, distributions, statistical inference, regression analysis, machine learning methods, and the use of Monte Carlo simulation for dynamic stochastic models. Ultimately this text introduces the Julia programming language as a computational tool, uniquely addressing end-users rather than developers. It makes heavy use of over 200 code examples to illustrate dozens of key statistical concepts. The Julia code, written in a simple format with parameters that can be easily modified, is also available for download from the book’s associated GitHub repository online.See what co-creators of the Julia language are saying about the book:Professor Alan Edelman, MIT: With “Statistics with Julia”, Yoni and Hayden have written an easy to read, well organized, modern introduction to statistics. The code may be looked at, and understood on the static pages of a book, or even better, when running live on a computer. Everything you need is here in one nicely written self-contained reference. Dr. Viral Shah, CEO of Julia Computing: Yoni and Hayden provide a modern way to learn statistics with the Julia programming language. This book has been perfected through iteration over several semesters in the classroom. It prepares the reader with two complementary skills - statistical reasoning with hands on experience and working with large datasets through training in Julia.
Statistics with Posterior Probability and a PHC Curve
by Hideki ToyodaThis textbook reconstructs the statistics curriculum from the perspective of posterior probability. In recent years, there have been several reports that the results of studies using significant tests cannot be reproduced. It is a problem called a “reproducibility crisis”. For example, suppose we could reject the null hypothesis that “the average number of days to recovery in patients who took a new drug was the same as that in the control group”. However, rejecting the null hypothesis is only a necessary condition for the new drug to be effective. Even if the necessary conditions are met, it does not necessarily mean that the new drug is effective. In fact, there are many cases where the effect is not reproduced. Sufficient conditions should be presented, such as “the average number of days until recovery in patients who take new drugs is sufficiently short compared to the control group, evaluated from a medical point of view”, without paying attention to necessary conditions. This book reconstructs statistics from the perspective of PHC, i.e., probability that a research hypothesis is correct. For example, the PHC curve shows the posterior probability that the statement “The average number of days until recovery for patients taking a new drug is at least θ days shorter than that of the control group” is correct as a function of θ. Using the PHC curve makes it possible to discuss the sufficient conditions rather than the necessary conditions for being an efficient treatment. The value of statistical research should be evaluated with concrete indicators such as “90% probability of being at least 3 days shorter”, not abstract metrics like the p-value.
Statistics with R: A Beginner's Guide
by Robert StinerockThe dynamic, student focused textbook provides step-by-step instruction in the use of R and of statistical language as a general research tool. It is ideal for anyone hoping to: Complete an introductory course in statistics Prepare for more advanced statistical courses Gain the transferable analytical skills needed to interpret research from across the social sciences Learn the technical skills needed to present data visually Acquire a basic competence in the use of R. The book provides readers with the conceptual foundation to use applied statistical methods in everyday research. Each statistical method is developed within the context of practical, real-world examples and is supported by carefully developed pedagogy and jargon-free definitions. Theory is introduced as an accessible and adaptable tool and is always contextualized within the pragmatic context of real research projects and definable research questions. Author Robert Stinerock has also created a wide range of online resources, including: R scripts, complete solutions for all exercises, data files for each chapter, video and screen casts, and interactive multiple-choice quizzes.
Statistics with R: A Beginner's Guide
by Robert StinerockThe dynamic, student focused textbook provides step-by-step instruction in the use of R and of statistical language as a general research tool. It is ideal for anyone hoping to: Complete an introductory course in statistics Prepare for more advanced statistical courses Gain the transferable analytical skills needed to interpret research from across the social sciences Learn the technical skills needed to present data visually Acquire a basic competence in the use of R. The book provides readers with the conceptual foundation to use applied statistical methods in everyday research. Each statistical method is developed within the context of practical, real-world examples and is supported by carefully developed pedagogy and jargon-free definitions. Theory is introduced as an accessible and adaptable tool and is always contextualized within the pragmatic context of real research projects and definable research questions. Author Robert Stinerock has also created a wide range of online resources, including: R scripts, complete solutions for all exercises, data files for each chapter, video and screen casts, and interactive multiple-choice quizzes.
Statistics with R: A Beginner′s Guide
by Robert StinerockStatistics is made simple with this award-winning guide to using R and applied statistical methods. With a clear step-by-step approach explained using real world examples, learn the practical skills you need to use statistical methods in your research from an expert with over 30 years of teaching experience. With a wealth of hands-on exercises and online resources created by the author, practice your skills using the data sets and R scripts from the book with detailed screencasts that accompany each script. This book is ideal for anyone looking to: • Complete an introductory course in statistics • Prepare for more advanced statistical courses • Gain the transferable analytical skills needed to interpret research from across the social sciences • Learn the technical skills needed to present data visually • Acquire a basic competence in the use of R and RStudio. This edition also includes a gentle introduction to Bayesian methods integrated throughout. The author has created a wide range of online resources, including: over 90 R scripts, 36 datasets, 37 screen casts, complete solutions for all exercises, and 130 multiple-choice questions to test your knowledge.
Statistics with R: A Beginner′s Guide
by Robert StinerockStatistics is made simple with this award-winning guide to using R and applied statistical methods. With a clear step-by-step approach explained using real world examples, learn the practical skills you need to use statistical methods in your research from an expert with over 30 years of teaching experience. With a wealth of hands-on exercises and online resources created by the author, practice your skills using the data sets and R scripts from the book with detailed screencasts that accompany each script. This book is ideal for anyone looking to: • Complete an introductory course in statistics • Prepare for more advanced statistical courses • Gain the transferable analytical skills needed to interpret research from across the social sciences • Learn the technical skills needed to present data visually • Acquire a basic competence in the use of R and RStudio. This edition also includes a gentle introduction to Bayesian methods integrated throughout. The author has created a wide range of online resources, including: over 90 R scripts, 36 datasets, 37 screen casts, complete solutions for all exercises, and 130 multiple-choice questions to test your knowledge.
Statistics without Mathematics
by David J BartholomewThis is a book about the ideas that drive statistics. It is an ideal primer for students who need an introduction to the concepts of statistics without the added confusion of technical jargon and mathematical language. It introduces the intuitive thinking behind standard procedures, explores the process of informal reasoning, and uses conceptual frameworks to provide a foundation for students new to statistics. It showcases the expertise we have all developed from living in a data saturated society, increases our statistical literacy and gives us the tools needed to approach statistical mathematics with confidence. Key topics include: Variability Standard Distributions Correlation Relationship Sampling Inference An engaging, informal introduction this book sets out the conceptual tools required by anyone undertaking statistical procedures for the first time or for anyone needing a fresh perspective whilst studying the work of others.
Statistics without Mathematics
by David J BartholomewThis is a book about the ideas that drive statistics. It is an ideal primer for students who need an introduction to the concepts of statistics without the added confusion of technical jargon and mathematical language. It introduces the intuitive thinking behind standard procedures, explores the process of informal reasoning, and uses conceptual frameworks to provide a foundation for students new to statistics. It showcases the expertise we have all developed from living in a data saturated society, increases our statistical literacy and gives us the tools needed to approach statistical mathematics with confidence. Key topics include: Variability Standard Distributions Correlation Relationship Sampling Inference An engaging, informal introduction this book sets out the conceptual tools required by anyone undertaking statistical procedures for the first time or for anyone needing a fresh perspective whilst studying the work of others.
Statistics, 3E (Idiot's Guides)
by Robert A. Donnelly Fatma Abdel-RaoufStatistics is a class that is required in many college majors, and it&’s an increasingly popular Advanced Placement (AP) high school course. In addition to math and technical students, many business and liberal arts students are required to take it as a fundamental component of their majors. A knowledge of statistical interpretation is vital for many careers. Idiot&’s Guides®: Statistics explains the fundamental tenets in language anyone can understand. Content includes: - Calculating descriptive statistics. - Measures of central tendency: mean, median, and mode. - Probability. - Variance analysis. - Inferential statistics. - Hypothesis testing. - Organizing data into statistical charts and tables.
Statistics, New Empiricism and Society in the Era of Big Data (SpringerBriefs in Statistics)
by Giuseppe ArbiaThis book reveals the myriad aspects of Big Data collection and analysis, by defining and clarifying the meaning of Big Data and its unique characteristics in a non-technical and easy-to-follow way. Moreover, it discusses critical issues and problems related to the Big Data revolution and their implications for both Statistics as a discipline and for our everyday lives. The author identifies various problems and limitations in the quantitative analysis of Big Data, with regard to e.g. its volume, velocity and variety, as well as its reliability and veridicity. Dedicated chapters focus on the epistemological aspects of data-based knowledge and ethical aspects of the use of Big Data, while also addressing paradigmatic cases such as Cambridge Analytica and the use of data from social networks to influence election outcomes.
Statistics, Society and Environment: 35th FNE, Cuernavaca, Mexico, September 27-29, 2023 (Springer Proceedings in Mathematics & Statistics #479)
by Ruth Fuentes-García J. Andrés Christen Gabriel Núñez-Antonio Sergio Pérez Alan Riva-PalacioThis volume features a collection of peer-reviewed contributions from the biannual conference organized by the Mexican Statistical Society, held in Cuernavaca, Mexico, from September 27-29, 2023. Statistical research in Latin America is vibrant and far-reaching, with extensive networks both within the region and beyond. However, much of this work is published in Spanish, limiting access for a broader audience. This volume aims to bridge that gap by presenting selected research from Latin American scholars and their collaborators to a wider readership. Academics will find value in the latest methodological advancements, while practitioners from various fields may discover innovative tools for data analysis. The volume places special emphasis on environmental statistics and applications that address societal issues or directly model social phenomena.
Statistics, Testing, and Defense Acquisition: New Approaches and Methodological Improvements
by Panel on Statistical Methods for Testing Evaluating Defense SystemsFor every weapons system being developed, the U.S. Department of Defense (DOD) must make a critical decision: Should the system go forward to full-scale production? The answer to that question may involve not only tens of billions of dollars but also the nation's security and military capabilities. In the milestone process used by DOD to answer the basic acquisition question, one component near the end of the process is operational testing, to determine if a system meets the requirements for effectiveness and suitability in realistic battlefield settings. Problems discovered at this stage can cause significant production delays and can necessitate costly system redesign.This book examines the milestone process, as well as the DOD's entire approach to testing and evaluating defense systems. It brings to the topic of defense acquisition the application of scientific statistical principles and practices.
Statistics: 1,001 Practice Problems For Dummies (+ Free Online Practice)
by Consumer Dummies1,001 practice opportunities to score higher in statistics 1,001 Statistics Practice Problems For Dummies takes you beyond the instruction and guidance offered in Statistics For Dummies to give you a more hands-on understanding of statistics. The practice problems offered range in difficulty, including detailed explanations and walk-throughs. In this series, every step of every solution is shown with explanations and detailed narratives to help you solve each problem. With the book purchase, you'll also get access to practice statistics problems online. This content features 1,001 practice problems presented in multiple choice format; on-the-go access from smart phones, computers, and tablets; customizable practice sets for self-directed study; practice problems categorized as easy, medium, or hard; and a one-year subscription with book purchase. Offers on-the-go access to practice statistics problems Gives you friendly, hands-on instruction 1,001 statistics practice problems that range in difficulty 1,001 Statistics Practice Problems For Dummies provides ample practice opportunities for students who may have taken statistics in high school and want to review the most important concepts as they gear up for a faster-paced college class.
Statistics: 1001 Practice Problems For Dummies (+ Free Online Practice)
by The Experts at DummiesBecome more likely to succeed—gain stats mastery with Dummies Statistics: 1001 Practice Problems For Dummies gives you 1,001 opportunities to practice solving problems from all the major topics covered in Statistics classes—in the book and online! Get extra help with tricky subjects, solidify what you’ve already learned, and get in-depth walk-throughs for every problem with this useful book. These practice problems and detailed answer explanations will help you gain a valuable working knowledge of statistics, no matter what your skill level. Thanks to Dummies, you have a resource to help you put key stats concepts into practice. Work through practice problems on all Statistics topics covered in school classes Read through detailed explanations of the answers to build your understanding Access practice questions online to study anywhere, any time Improve your grade and up your study game with practice, practice, practiceThe material presented in Statistics: 1001 Practice Problems For Dummies is an excellent resource for students, as well as parents and tutors looking to help supplement Statistics instruction. Statistics: 1001 Practice Problems For Dummies (9781119883593) was previously published as 1,001 Statistics Practice Problems For Dummies (9781118776049). While this version features a new Dummies cover and design, the content is the same as the prior release and should not be considered a new or updated product.
Statistics: A Concise Mathematical Introduction for Students, Scientists, and Engineers (Wiley Series In Probability And Statistics Ser. #551)
by David W. ScottStatistic: A Concise Mathematical Introduction for Students and Scientists offers a one academic term text that prepares the student to broaden their skills in statistics, probability and inference, prior to selecting their follow-on courses in their chosen fields, whether it be engineering, computer science, programming, data sciences, business or economics. The book places focus early on continuous measurements, as well as discrete random variables. By invoking simple and intuitive models and geometric probability, discrete and continuous experiments and probabilities are discussed throughout the book in a natural way. Classical probability, random variables, and inference are discussed, as well as material on understanding data and topics of special interest. Topics discussed include: • Classical equally likely outcomes • Variety of models of discrete and continuous probability laws • Likelihood function and ratio • Inference • Bayesian statistics With the growth in the volume of data generated in many disciplines that is enabling the growth in data science, companies now demand statistically literate scientists and this textbook is the answer, suited for undergraduates studying science or engineering, be it computer science, economics, life sciences, environmental, business, amongst many others. Basic knowledge of bivariate calculus, R language, Matematica and JMP is useful, however there is an accompanying website including sample R and Mathematica code to help instructors and students.
Statistics: A Gentle Introduction
by Frederick L. CoolidgeDoing statistics for the first time? Don't panic says Professor Fred Coolidge. In Statistics: A Gentle Introduction, Second Edition, he shows how statistics needn't be difficult or dull. Dr. Coolidge likens the role of a statistician to that of a curious detective, an honest attorney, and a good storyteller. He minimizes the use of formulas, but provides a step-by-step approach to their solution, and includes a glossary of key terms, symbols, and definitions at the end of each chapter. Every chapter also includes a short story about historical and contemporary statisticians who figured prominently in the evolution of the discipline of statistics. This second edition includes specific suggestions as to the detection of baloney, that is, fraudulent claims and questionable studies.
Statistics: A Gentle Introduction
by Frederick L. CoolidgeThe Fourth Edition of Statistics: A Gentle Introduction shows students that an introductory statistics class doesn’t need to be difficult or dull. This text minimizes students’ anxieties about math by explaining the concepts of statistics in plain language first, before addressing the math. Each formula within the text has a step-by-step example to demonstrate the calculation so students can follow along. Only those formulas that are important for final calculations are included in the text so students can focus on the concepts, not the numbers. A wealth of real-world examples and applications gives a context for statistics in the real world and how it helps us solve problems and make informed choices. New to the Fourth Edition are sections on working with big data, new coverage of alternative non-parametric tests, beta coefficients, and the "nocebo effect," discussions of p values in the context of research, an expanded discussion of confidence intervals, and more exercises and homework options under the new feature "Test Yourself." Included with this title: The password-protected Instructor Resource Site (formally known as SAGE Edge) offers access to all text-specific resources, including a test bank and editable, chapter-specific PowerPoint® slides.