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Book Elementary Computer Programs for Statistical Analysis

Download or read book Elementary Computer Programs for Statistical Analysis written by James P. Barrett and published by Brooks/Cole. This book was released on 1971 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book STAT

    Book Details:
  • Author : R. S. Hall
  • Publisher :
  • Release : 1966
  • ISBN :
  • Pages : pages

Download or read book STAT written by R. S. Hall and published by . This book was released on 1966 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Software for Data Analysis

    Book Details:
  • Author : John Chambers
  • Publisher : Springer Science & Business Media
  • Release : 2008-06-14
  • ISBN : 0387759360
  • Pages : 515 pages

Download or read book Software for Data Analysis written by John Chambers and published by Springer Science & Business Media. This book was released on 2008-06-14 with total page 515 pages. Available in PDF, EPUB and Kindle. Book excerpt: John Chambers turns his attention to R, the enormously successful open-source system based on the S language. His book guides the reader through programming with R, beginning with simple interactive use and progressing by gradual stages, starting with simple functions. More advanced programming techniques can be added as needed, allowing users to grow into software contributors, benefiting their careers and the community. R packages provide a powerful mechanism for contributions to be organized and communicated. This is the only advanced programming book on R, written by the author of the S language from which R evolved.

Book Elementary Data Analysis Using Microsoft Excel

Download or read book Elementary Data Analysis Using Microsoft Excel written by Anita Meehan and published by McGraw-Hill Humanities/Social Sciences/Languages. This book was released on 1999-07-30 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Elementary Data Analysis by Meehan and Warner introduces students to Microsoft Excel spreadsheets as a tool to be used in Introductory Statistics courses. For years professors have relied on specialized statistical software like SPSS (Statistical Package for Social Sciences) in statistics and research methods courses, but computer technology has become ubiquitous and spreadsheets more popular. This easy to use workbook demonstrates that by utilizing a familiar program such as Excel, students can concentrate more on statistical concepts and outcomes and less on the mechanics of the software. Even for students who are not familiar with spreadsheets, they can learn statistical analysis easier with Excel than with specialized software, and this workbook takes them through step by step.

Book Basic Statistical Analysis Using RStudio Software

Download or read book Basic Statistical Analysis Using RStudio Software written by Wan Muhamad Amir W Ahmad, Farah Muna Mohamad Ghazali, Muhammad Azeem Yaqoob and published by Penerbit USM. This book was released on 2023-01-01 with total page 161 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Basic Elements of Computational Statistics

Download or read book Basic Elements of Computational Statistics written by Wolfgang Karl Härdle and published by Springer. This book was released on 2017-09-29 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook on computational statistics presents tools and concepts of univariate and multivariate statistical data analysis with a strong focus on applications and implementations in the statistical software R. It covers mathematical, statistical as well as programming problems in computational statistics and contains a wide variety of practical examples. In addition to the numerous R sniplets presented in the text, all computer programs (quantlets) and data sets to the book are available on GitHub and referred to in the book. This enables the reader to fully reproduce as well as modify and adjust all examples to their needs. The book is intended for advanced undergraduate and first-year graduate students as well as for data analysts new to the job who would like a tour of the various statistical tools in a data analysis workshop. The experienced reader with a good knowledge of statistics and programming might skip some sections on univariate models and enjoy the various ma thematical roots of multivariate techniques. The Quantlet platform quantlet.de, quantlet.com, quantlet.org is an integrated QuantNet environment consisting of different types of statistics-related documents and program codes. Its goal is to promote reproducibility and offer a platform for sharing validated knowledge native to the social web. QuantNet and the corresponding Data-Driven Documents-based visualization allows readers to reproduce the tables, pictures and calculations inside this Springer book.

Book Elementary Programming for Statistics

Download or read book Elementary Programming for Statistics written by Richard A. Lyczak and published by Brooks/Cole. This book was released on 1980 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book SAS for Data Analysis

    Book Details:
  • Author : Mervyn G. Marasinghe
  • Publisher : Springer Science & Business Media
  • Release : 2008-12-10
  • ISBN : 038777372X
  • Pages : 562 pages

Download or read book SAS for Data Analysis written by Mervyn G. Marasinghe and published by Springer Science & Business Media. This book was released on 2008-12-10 with total page 562 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is intended for use as the textbook in a second course in applied statistics that covers topics in multiple regression and analysis of variance at an intermediate level. Generally, students enrolled in such courses are p- marily graduate majors or advanced undergraduate students from a variety of disciplines. These students typically have taken an introductory-level s- tistical methods course that requires the use a software system such as SAS for performing statistical analysis. Thus students are expected to have an - derstanding of basic concepts of statistical inference such as estimation and hypothesis testing. Understandably, adequate time is not available in a ?rst course in stat- tical methods to cover the use of a software system adequately in the amount of time available for instruction. The aim of this book is to teach how to use the SAS system for data analysis. The SAS language is introduced at a level of sophistication not found in most introductory SAS books. Important features such as SAS data step programming, pointers, and line-hold spe- ?ers are described in detail. The powerful graphics support available in SAS is emphasized throughout, and many worked SAS program examples contain graphic components.

Book Developing Statistical Software in Fortran 95

Download or read book Developing Statistical Software in Fortran 95 written by David R. Lemmon and published by Springer Science & Business Media. This book was released on 2005-05-06 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many books teach computational statistics. Until now, however, none has shown how to write a good program. This book gives statisticians, biostatisticians and methodologically-oriented researchers the tools they need to develop high-quality statistical software. Topics include how to: Program in Fortran 95 using a pseudo object-oriented style Write accurate and efficient computational procedures Create console applications Build dynamic-link libraries (DLLs) and Windows-based software components Develop graphical user interfaces (GUIs) Through detailed examples, readers are shown how to call Fortran procedures from packages including Excel, SAS, SPSS, S-PLUS, R, and MATLAB. They are even given a tutorial on creating GUIs for Fortran computational code using Visual Basic.NET. This book is for those who want to learn how to create statistical applications quickly and effectively. Prior experience with a programming language such as Basic, Fortran or C is helpful but not required. More experienced programmers will learn new strategies to harness the power of modern Fortran and the object-oriented paradigm. This may serve as a supplementary text for a graduate course on statistical computing. From the reviews: "This book should be read by all statisticians, engineers, and scientists who want to implement an algorithm as a computer program. The book is the best introduction to programming that I have ever read. I value it as one of my important reference books in my personal library." Melvin J. Hinich for Techonmetrics, November 2006 "Overall, the book is well written and provides a reasonable introduction to the use of modern versions of Fortran for statistical computation. The real thrust of the book is building COM interfaces using Fortran, and it will no doubt be most useful to anyone who needs to build such interfaces." Journal of the American Statistical Association, June 2006 "The book is well written and is divided into chapters and sections which are coherent...Overall the book seems like a good resource for someone that already knows some dialect of FORTRAN and wants to learn a bit about what is new in FORTRAN 95..." Robert Gentleman for the Journal of Statistical Software, December 2006

Book The R Software

    Book Details:
  • Author : Pierre Lafaye de Micheaux
  • Publisher : Springer Science & Business
  • Release : 2014-05-13
  • ISBN : 1461490200
  • Pages : 654 pages

Download or read book The R Software written by Pierre Lafaye de Micheaux and published by Springer Science & Business. This book was released on 2014-05-13 with total page 654 pages. Available in PDF, EPUB and Kindle. Book excerpt: The contents of The R Software are presented so as to be both comprehensive and easy for the reader to use. Besides its application as a self-learning text, this book can support lectures on R at any level from beginner to advanced. This book can serve as a textbook on R for beginners as well as more advanced users, working on Windows, MacOs or Linux OSes. The first part of the book deals with the heart of the R language and its fundamental concepts, including data organization, import and export, various manipulations, documentation, plots, programming and maintenance. The last chapter in this part deals with oriented object programming as well as interfacing R with C/C++ or Fortran, and contains a section on debugging techniques. This is followed by the second part of the book, which provides detailed explanations on how to perform many standard statistical analyses, mainly in the Biostatistics field. Topics from mathematical and statistical settings that are included are matrix operations, integration, optimization, descriptive statistics, simulations, confidence intervals and hypothesis testing, simple and multiple linear regression, and analysis of variance. Each statistical chapter in the second part relies on one or more real biomedical data sets, kindly made available by the Bordeaux School of Public Health (Institut de Santé Publique, d'Épidémiologie et de Développement - ISPED) and described at the beginning of the book. Each chapter ends with an assessment section: memorandum of most important terms, followed by a section of theoretical exercises (to be done on paper), which can be used as questions for a test. Moreover, worksheets enable the reader to check his new abilities in R. Solutions to all exercises and worksheets are included in this book.

Book Statistical Analysis

Download or read book Statistical Analysis written by Abdelmonem A. Afifi and published by . This book was released on 1979 with total page 468 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to data analysis; Elementary statistical inference; Regression and correlation analysis; The analysis of variance; Multivariate statistical methods; Review of fundamental concepts.

Book Basic Statistics

    Book Details:
  • Author : Tenko Raykov
  • Publisher : Rowman & Littlefield Publishers
  • Release : 2012-10-04
  • ISBN : 1442218487
  • Pages : 346 pages

Download or read book Basic Statistics written by Tenko Raykov and published by Rowman & Littlefield Publishers. This book was released on 2012-10-04 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: Basic Statistics provides an accessible and comprehensive introduction to statistics using the free, state-of-the-art, powerful software program R. This book is designed to both introduce students to key concepts in statistics and to provide simple instructions for using R. This concise book: Teaches essential concepts in statistics, assuming little background knowledge on the part of the reader Introduces students to R with as few sub-commands as possible for ease of use Provides practical examples from the educational, behavioral, and social sciences With clear explanations of statistical processes and step-by-step commands in R, Basic Statistics will appeal to students and professionals across the social and behavioral sciences.

Book Basic Statistical Methods and Models for the Sciences

Download or read book Basic Statistical Methods and Models for the Sciences written by Judah Rosenblatt and published by CRC Press. This book was released on 2017-07-12 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: The use of statistics in biology, medicine, engineering, and the sciences has grown dramatically in recent years and having a basic background in the subject has become a near necessity for students and researchers in these fields. Although many introductory statistics books already exist, too often their focus leans towards theory and few help readers gain effective experience in using a standard statistical software package. Designed to be used in a first course for graduate or upper-level undergraduate students, Basic Statistical Methods and Models builds a practical foundation in the use of statistical tools and imparts a clear understanding of their underlying assumptions and limitations. Without getting bogged down in proofs and derivations, thorough discussions help readers understand why the stated methods and results are reasonable. The use of the statistical software Minitab is integrated throughout the book, giving readers valuable experience with computer simulation and problem-solving techniques. The author focuses on applications and the models appropriate to each problem while emphasizing Monte Carlo methods, the Central Limit Theorem, confidence intervals, and power functions. The text assumes that readers have some degree of maturity in mathematics, but it does not require the use of calculus. This, along with its very clear explanations, generous number of exercises, and demonstrations of the extensive uses of statistics in diverse areas applications make Basic Statistical Methods and Models highly accessible to students in a wide range of disciplines.

Book Mathematical Statistics with Applications

Download or read book Mathematical Statistics with Applications written by William Mendenhall and published by Brooks/Cole. This book was released on 1973 with total page 676 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book NBS Special Publication

Download or read book NBS Special Publication written by and published by . This book was released on 1978 with total page 476 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Resources in Education

Download or read book Resources in Education written by and published by . This book was released on 1998 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book An Introduction to Statistical Learning

Download or read book An Introduction to Statistical Learning written by Gareth James and published by Springer Nature. This book was released on 2023-08-01 with total page 617 pages. Available in PDF, EPUB and Kindle. Book excerpt: An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance, marketing, and astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. This book is targeted at statisticians and non-statisticians alike, who wish to use cutting-edge statistical learning techniques to analyze their data. Four of the authors co-wrote An Introduction to Statistical Learning, With Applications in R (ISLR), which has become a mainstay of undergraduate and graduate classrooms worldwide, as well as an important reference book for data scientists. One of the keys to its success was that each chapter contains a tutorial on implementing the analyses and methods presented in the R scientific computing environment. However, in recent years Python has become a popular language for data science, and there has been increasing demand for a Python-based alternative to ISLR. Hence, this book (ISLP) covers the same materials as ISLR but with labs implemented in Python. These labs will be useful both for Python novices, as well as experienced users.