Der blev fundet 429 produkter som matchede din søgning efter statistical i 17 butikker:

Understanding the world of R programming and analysis has never been easier Most guides to R, whether books or online, focus on R functions and procedures. But now, thanks to Statistical Analysis with R For Dummies, you have access to a trusted, easy-to-follow guide that focuses on the foundational statistical concepts that R addresses as well as step-by-step guidance that shows you exactly how to implement them using R programming. People are becoming more aware of R every day as major institutions are adopting it as a standard. Part of its appeal is that it's a free tool that's taking the place of costly statistical software packages that sometimes take an inordinate amount of time to learn. Plus, R enables a user to carry out complex statistical analyses by simply entering a few commands, making sophisticated analyses available and understandable to a wide audience. Statistical Analysis with R For Dummies enables you to perform these analyses and to fully understand their implications and results. Gets you up to speed on the #1 analytics/data science software tool Demonstrates how to easily find, download, and use cutting-edge community-reviewed methods in statistics and predictive modeling Shows you how R offers intel from leading researchers in data science, free of charge Provides information on using R Studio to work with R Get ready to use R to crunch and analyze your data the fast and easy way!

DUX Ritzy 3 Pers. Sofa L: 210 cm - Chrome/Elmo Rustical Skøn 3-personers sofa fra Dux. Med Ritzy sofaens rene linjer og minimalistiske udtryk er denne et siddemøbel, som vil tilføre elegance til boligen såvel som kontoret. Sofaen har en smukt udført bagside med subtile detaljer i dens design, som opfordrer til at lade den stå frit i rummet. Med sofaens sædehynder med DUX Pascal spiralsystem og rygpuder i koldskum, som er betrukket med lækkert blødt Naturale læder, der er polstret med knapsyning, er Ritzy et siddemøbel, hvor komfort, design og kvalitet går op i en højere enhed. Ritzy sofaen fås i flere farver, ligesom Ritzy serien også rummer både 2 pers. sofaer og lænestole, som man med fordel kan kombinere sin sofa med for at opnå et fuldendt look af siddemøbler i stuen. OBS: Første miljøbillede er mest retvisende i henhold til at gengive denne vares farve. Designer: Dux Design Team Materialer: Rustfrit stål Læder (Elmo Rustical) Mål: Bredde: 210 cm Dybde: 80 cm Højde: 85 cm Sædehøjde: 42 cm Armlænshøjde: 73 cm Farve: Krom Grå

NOW A MAJOR NETFLIX FILM STARRING HALEY LU RICHARDSONWho would have guessed that four minutes could change everything?Today should be one of the worst days of Hadley's life. Her father is getting married in London to a woman she's never even met, and she's just missed her flight.Hadley has never believed in destiny or fate before. But, stuck at the airport in New York, today is also the day she meets Oliver. He's British. He's cute. And he's on her new flight.Set over twenty-four hours, Hadley and Oliver's story will make you believe that true love finds you when you're least expecting it.Readers love The Statistical Probability of Love at First Sight'A warm and witty book about destiny, first loves, soul mates and perfect timing' 5* reader review'One of those books that you just want to keep reading and reading' 5* reader review'So amazing! A beautiful love story' 5* reader review

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Statistical Rethinking: A Bayesian Course with Examples in R and Stan builds your knowledge of and confidence in making inferences from data. Reflecting the need for scripting in today's model-based statistics, the book pushes you to perform step-by-step calculations that are usually automated. This unique computational approach ensures that you understand enough of the details to make reasonable choices and interpretations in your own modeling work.The text presents causal inference and generalized linear multilevel models from a simple Bayesian perspective that builds on information theory and maximum entropy. The core material ranges from the basics of regression to advanced multilevel models. It also presents measurement error, missing data, and Gaussian process models for spatial and phylogenetic confounding.The second edition emphasizes the directed acyclic graph (DAG) approach to causal inference, integrating DAGs into many examples. The new edition also contains new material on the design of prior distributions, splines, ordered categorical predictors, social relations models, cross-validation, importance sampling, instrumental variables, and Hamiltonian Monte Carlo. It ends with an entirely new chapter that goes beyond generalized linear modeling, showing how domain-specific scientific models can be built into statistical analyses.Features Integrates working code into the main text Illustrates concepts through worked data analysis examples Emphasizes understanding assumptions and how assumptions are reflected in code Offers more detailed explanations of the mathematics in optional sections Presents examples of using the dagitty R package to analyze causal graphs Provides the rethinking R package on the author's website and on GitHub

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Statistical Analysis of Questionnaires: A Unified Approach Based on R and Stata presents special statistical methods for analyzing data collected by questionnaires. The book takes an applied approach to testing and measurement tasks, mirroring the growing use of statistical methods and software in education, psychology, sociology, and other fields. It is suitable for graduate students in applied statistics and psychometrics and practitioners in education, health, and marketing. The book covers the foundations of classical test theory (CTT), test reliability, validity, and scaling as well as item response theory (IRT) fundamentals and IRT for dichotomous and polytomous items. The authors explore the latest IRT extensions, such as IRT models with covariates, multidimensional IRT models, IRT models for hierarchical and longitudinal data, and latent class IRT models. They also describe estimation methods and diagnostics, including graphical diagnostic tools, parametric and nonparametric tests, and differential item functioning. Stata and R software codes are included for each method. To enhance comprehension, the book employs real datasets in the examples and illustrates the software outputs in detail. The datasets are available on the authors’ web page.

LK Hjelle Siesta Fiora Lænestol Høj - Black/Elmo Rustical Blue SIESTA FIORA imponerer med sin iøjnefaldende, skulpturelle silhuet, der giver stilen et elegant og strømlinet udseende. Dette gør den nem at tilpasse ethvert rum uden at gå på kompromis med sin fantastisk komfort og unikke karakter. Lanceret i 2005 for at fejre Siestas 40-års jubilæum, står SIESTA FIORA som et ikon der forener enkelthed, minimalisme og funktionalitet i én stol. Den kendte stol er designet af Ingmar Relling som altid lagde vægt på forholdet mellem design og funktion, hvilket også tydeligt ses i Siesta Fiora. Stolen fås i forskellige farver og variationer. Høj uden armlæn, høj med armlæn og lav uden armlæn. Den kommer i flotte farver, hvor mange af dem er varme og nemme at tilføje til eksisterende indretninger. Fodskammel kan tilkøbes. Bemærk: Elmo Rustical læderet er behandlet i begrænset omfang, udover garvning og farvning. Hvert stykke læder er unikt og ar samt mærker fra for eksempel insektbid kan forekomme ligeledes kan der forekomme en tydelig struktur. Med tiden danner læderet en smuk naturlig patina. Det anbefales at vedligeholde læderet regelmæssigt. Designer: Ingmar Relling Materialer: Ramme af sortlakeret eg Sort canvas Læder: Elmo Rustical - anilin Mål: Højde: 100 cm Bredde: 62 cm Dybde: 85 cm Sædehøjde: 43 cm Farve: Black/Blue

Statistical Process Control has been the World Class way to run production processes for 100 years. Now that most volume manufacturing has moved to lost cost countries Western manufacturing is left with Low Volume high value products. How can Statistical Process Control still function and flourish in these small batch production Businesses? In fact the answer is how can you possibly run in a small batch environment without Statistical Process Control?

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Mounting failures of replication in social and biological sciences give a new urgency to critically appraising proposed reforms. This book pulls back the cover on disagreements between experts charged with restoring integrity to science. It denies two pervasive views of the role of probability in inference: to assign degrees of belief, and to control error rates in a long run. If statistical consumers are unaware of assumptions behind rival evidence reforms, they can't scrutinize the consequences that affect them (in personalized medicine, psychology, etc.). The book sets sail with a simple tool: if little has been done to rule out flaws in inferring a claim, then it has not passed a severe test. Many methods advocated by data experts do not stand up to severe scrutiny and are in tension with successful strategies for blocking or accounting for cherry picking and selective reporting. Through a series of excursions and exhibits, the philosophy and history of inductive inference come alive. Philosophical tools are put to work to solve problems about science and pseudoscience, induction and falsification.

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This book provides an introduction to computer-based methods for the analysis of genomic data. Breakthroughs in molecular and computational biology have contributed to the emergence of vast data sets, where millions of genetic markers for each individual are coupled with medical records, generating an unparalleled resource for linking human genetic variation to human biology and disease. Similar developments have taken place in animal and plant breeding, where genetic marker information is combined with production traits. An important task for the statistical geneticist is to adapt, construct and implement models that can extract information from these large-scale data. An initial step is to understand the methodology that underlies the probability models and to learn the modern computer-intensive methods required for fitting these models. The objective of this book, suitable for readers who wish to develop analytic skills to perform genomic research, is to provide guidance to take this first step. This book is addressed to numerate biologists who typically lack the formal mathematical background of the professional statistician. For this reason, considerably more detail in explanations and derivations is offered. It is written in a concise style and examples are used profusely. A large proportion of the examples involve programming with the open-source package R. The R code needed to solve the exercises is provided. The MarkDown interface allows the students to implement the code on their own computer, contributing to a better understanding of the underlying theory. Part I presents methods of inference based on likelihood and Bayesian methods, including computational techniques for fitting likelihood and Bayesian models. Part II discusses prediction for continuous and binary data using both frequentist and Bayesian approaches. Some of the models used for prediction are also used for gene discovery. The challenge is to find promising genes without incurring a large proportion of false positive results. Therefore, Part II includes a detour on False Discovery Rate assuming frequentist and Bayesian perspectives. The last chapter of Part II provides an overview of a selected number of non-parametric methods. Part III consists of exercises and their solutions. Daniel Sorensen holds PhD and DSc degrees from the University of Edinburgh and is an elected Fellow of the American Statistical Association. He was professor of Statistical Genetics at Aarhus University where, at present, he is professor emeritus.

STATISTICAL METHODS FOR PSYCHOLOGY, 8E, International Edition surveys the statistical techniques commonly used in the behavioral and social sciences, especially psychology and education. To help students gain a better understanding of the specific statistical hypothesis tests that are covered throughout the text, author David Howell emphasize conceptual understanding. Along with significantly updated discussions of effect size and meta-analysis, this Eighth Edition continues to focus on two key themes that are the cornerstones of this book's success: the importance of looking at the data before beginning a hypothesis test, and the importance of knowing the relationship between the statistical test in use and the theoretical questions being asked by the experiment.

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Models and likelihood are the backbone of modern statistics. This 2003 book gives an integrated development of these topics that blends theory and practice, intended for advanced undergraduate and graduate students, researchers and practitioners. Its breadth is unrivaled, with sections on survival analysis, missing data, Markov chains, Markov random fields, point processes, graphical models, simulation and Markov chain Monte Carlo, estimating functions, asymptotic approximations, local likelihood and spline regressions as well as on more standard topics such as likelihood and linear and generalized linear models. Each chapter contains a wide range of problems and exercises. Practicals in the S language designed to build computing and data analysis skills, and a library of data sets to accompany the book, are available over the Web.

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Advances in computers and biotechnology have had a profound impact on biomedical research, and as a result complex data sets can now be generated to address extremely complex biological questions. Correspondingly, advances in the statistical methods necessary to analyze such data are following closely behind the advances in data generation methods. The statistical methods required by bioinformatics present many new and difficult problems for the research community. This book provides an introduction to some of these new methods. The main biological topics treated include sequence analysis, BLAST, microarray analysis, gene finding, and the analysis of evolutionary processes. The main statistical techniques covered include hypothesis testing and estimation, Poisson processes, Markov models and Hidden Markov models, and multiple testing methods. The second edition features new chapters on microarray analysis and on statistical inference, including a discussion of ANOVA, and discussions of the statistical theory of motifs and methods based on the hypergeometric distribution. Much material has been clarified and reorganized. The book is written so as to appeal to biologists and computer scientists who wish to know more about the statistical methods of the field, as well as to trained statisticians who wish to become involved with bioinformatics. The earlier chapters introduce the concepts of probability and statistics at an elementary level, but with an emphasis on material relevant to later chapters and often not covered in standard introductory texts. Later chapters should be immediately accessible to the trained statistician. Sufficient mathematical background consists of introductory courses in calculus and linear algebra. The basic biological concepts that are used are explained, or can be understood from the context, and standard mathematical concepts are summarized in an Appendix. Problems are provided at the end of each chapter allowing the reader to develop aspects of the theory outlined in the main text. Warren J. Ewens holds the Christopher H. Brown Distinguished Professorship at the University of Pennsylvania. He is the author of two books, Population Genetics and Mathematical Population Genetics. He is a senior editor of Annals of Human Genetics and has served on the editorial boards of Theoretical Population Biology, GENETICS, Proceedings of the Royal Society B and SIAM Journal in Mathematical Biology. He is a fellow of the Royal Society and the Australian Academy of Science. Gregory R. Grant is a senior bioinformatics researcher in the University of Pennsylvania Computational Biology and Informatics Laboratory. He obtained his Ph.D. in number theory from the University of Maryland in 1995 and his Masters in Computer Science from the University of Pennsylvania in 1999. Comments on the first edition: "This book would be an ideal text for a postgraduate course...[and] is equally well suited to individual study.... I would recommend the...

Moderne kvadratisk sofabord med fire sektioner Dette sofabord imponerer med sin unikke design, der kombinerer en varm, lysbrun bordplade i fire sektioner med et sort stel og ben. Sofabordet er håndlavet og derfor helt unikt, og den naturlige træmasering giver det et rustikt og charmerende udtryk. Dimensioner: Bredde: 60 cm Dybde: 60 cm Højde: 40 cm Mål pr. sektion på bordpladen (BxT): 29 x 29 cm Trætykkelse: ca. 1 cm MDF-tykkelse: ca. 5, 5 mm Se yderligere dimensioner i målskitse Farve: Bordplade: Varm lysbrun Stel og ben: Sort Funktioner: Håndlavet og unikt: Hvert sofabord er håndlavet og derfor helt unikt. Moderne design: Den kvadratiske form og den harmoniske farvekombination giver sofabordet et moderne og stilfuldt look. Praktisk bordplade: Den opdelte bordplade giver plads til snacks, drikkevarer, bøger og dekoration. Robust stel: Det sorte stel og de fire ben sikrer stabilitet og soliditet. Let at flytte: Sofabordet er indvendigt hul, hvilket gør det let at flytte rundt efter behov. Beskyttelse af gulvet: Anti-slip puder under benene beskytter dit gulv mod ridser. Anbefalet maksimal belastning: 20 kg Materialer: Bordplade: Massivt akacietræ, med klarlak Stel: Laikeret MDF Ben: Laikeret jern Leveringsindhold: Et sofabord uden dekoration Monteringsvejledning og -materiale medfølger Montering: Sofabordet leveres delvist samlet - kun benene skal monteres. Montering er nem og kan nemt udføres ved hjælp af den medfølgende vejledning. Plejevejledning: Rengør overfladen med en lunken, fugtig klud af bomuld. Undgå brug af skuremidler, skarpe rengøringsmidler eller dryppende våde klude. Bemærkninger: Træmaseringen og -strukturen er et naturligt træk ved træet og kan variere fra bord til bord. Akacietræ er et hårdt og holdbart træ, der er ideelt til fremstilling af møbler.