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Author: Jerry Glynn
Publisher: Cambridge University Press
Published: 2000-01-13
Total Pages: 496
ISBN-13: 9780521777698
DOWNLOAD EBOOKThis hugely successful textbook covers all the new features of Mathematica Version 4.
Author: David McMahon
Publisher: CRC Press
Published: 2006-01-13
Total Pages: 736
ISBN-13: 1420010395
DOWNLOAD EBOOKBecause of its large command structure and intricate syntax, Mathematica can be difficult to learn. Wolfram's Mathematica manual, while certainly comprehensive, is so large and complex that when trying to learn the software from scratch -- or find answers to specific questions -- one can be quickly overwhelmed. A Beginner's Guide to Mathemat
Author: Michael Trott
Publisher: Springer Science & Business Media
Published: 2006-10-27
Total Pages: 1243
ISBN-13: 0387288147
DOWNLOAD EBOOKProvides the reader with working knowledge of Mathematica and key aspects of Mathematica's numerical capabilities needed to deal with virtually any "real life" problem Clear organization, complete topic coverage, and an accessible writing style for both novices and experts Website for book with additional materials: http://www.MathematicaGuideBooks.org Accompanying DVD containing all materials as an electronic book with complete, executable Mathematica 5.1 compatible code and programs, rendered color graphics, and animations
Author: Alex Nordeen
Publisher: Guru99
Published: 2020-10-31
Total Pages: 349
ISBN-13:
DOWNLOAD EBOOKR is a programming language developed is widely used for statistical and graphical analysis. It can execute advance machine learning algorithms including earning algorithm, linear regression, time series, statistical inference. R programming language is used by Fortune 500 companies and tech bellwethers like Uber, Google, Airbnb, Facebook, Apple. R provides a data scientist tools and libraries (Dplyr) to perform the 3 steps of analysis 1) Extract 2) Transform, Cleanse 3) Analyze. Table of Contents Chapter 1: What is R Programming Language? Introduction & Basics Chapter 2: How to Download & Install R, RStudio, Anaconda on Mac or Windows Chapter 3: R Data Types, Arithmetic & Logical Operators with Example Chapter 4: R Matrix Tutorial: Create, Print, add Column, Slice Chapter 5: Factor in R: Categorical & Continuous Variables Chapter 6: R Data Frame: Create, Append, Select, Subset Chapter 7: List in R: Create, Select Elements with Example Chapter 8: R Sort a Data Frame using Order() Chapter 9: R Dplyr Tutorial: Data Manipulation(Join) & Cleaning(Spread) Chapter 10: Merge Data Frames in R: Full and Partial Match Chapter 11: Functions in R Programming (with Example) Chapter 12: IF, ELSE, ELSE IF Statement in R Chapter 13: For Loop in R with Examples for List and Matrix Chapter 14: While Loop in R with Example Chapter 15: apply(), lapply(), sapply(), tapply() Function in R with Examples Chapter 16: Import Data into R: Read CSV, Excel, SPSS, Stata, SAS Files Chapter 17: How to Replace Missing Values(NA) in R: na.omit & na.rm Chapter 18: R Exporting Data to Excel, CSV, SAS, STATA, Text File Chapter 19: Correlation in R: Pearson & Spearman with Matrix Example Chapter 20: R Aggregate Function: Summarise & Group_by() Example Chapter 21: R Select(), Filter(), Arrange(), Pipeline with Example Chapter 22: Scatter Plot in R using ggplot2 (with Example) Chapter 23: How to make Boxplot in R (with EXAMPLE) Chapter 24: Bar Chart & Histogram in R (with Example) Chapter 25: T Test in R: One Sample and Paired (with Example) Chapter 26: R ANOVA Tutorial: One way & Two way (with Examples) Chapter 27: R Simple, Multiple Linear and Stepwise Regression [with Example] Chapter 28: Decision Tree in R with Example Chapter 29: R Random Forest Tutorial with Example Chapter 30: Generalized Linear Model (GLM) in R with Example Chapter 31: K-means Clustering in R with Example Chapter 32: R Vs Python: What's the Difference? Chapter 33: SAS vs R: What's the Difference?
Author: Jeeva Jose
Publisher: KHANNA PUBLISHING HOUSE
Published:
Total Pages: 368
ISBN-13: 938617345X
DOWNLOAD EBOOKR programming is an efficient tool for statistical analysis of data. Data science has become critical to each field and the popularity of R is skyrocketing. Organization as large and diverse as Google, Facebook, Microsoft, Bank of America, Ford Motor Company, Mozilla, Thomas Cook, The New York Times, The National Weather Service, Twitter, ANZ Bank, Uber, Airbnb etc . have turned to R for reporting, analyzing and visualization of data, this book is for students and professionals of Mathematics, Statistics, Physics, Chemistry, Biology, Social Science and Medicine, Business, Engineering, Software, Information Technology, Sales, Bio Informatics, Pharmacy and any one, where data needs to be analyzed and represented graphically.
Author: Michael Trott
Publisher: Springer
Published: 2013-12-21
Total Pages: 1060
ISBN-13: 1441985034
DOWNLOAD EBOOKThis comprehensive, detailed reference provides readers with both a working knowledge of Mathematica in general and a detailed knowledge of the key aspects needed to create the fastest, shortest, and most elegant implementations possible. It gives users a deeper understanding of Mathematica by instructive implementations, explanations, and examples from a range of disciplines at varying levels of complexity. The three volumes -- Programming, Graphics, and Mathematics, total 3,000 pages and contain more than 15,000 Mathematica inputs, over 1,500 graphics, 4,000+ references, and more than 500 exercises. This first volume begins with the structure of Mathematica expressions, the syntax of Mathematica, its programming, graphic, numeric and symbolic capabilities. It then covers the hierarchical construction of objects out of symbolic expressions, the definition of functions, the recognition of patterns and their efficient application, program flows and program structuring, and the manipulation of lists. An indispensible resource for students, researchers and professionals in mathematics, the sciences, and engineering.
Author: Theodore W. Gray
Publisher: Addison Wesley Publishing Company
Published: 1992
Total Pages: 244
ISBN-13:
DOWNLOAD EBOOKTeaches new Mathematica users some of the important basics of this powerful software tool: defining functions, creating graphs and Notebooks, and applying useful problem-solving techniques. The authors cover 40 functions and use clear language and concise instructions to help readers master the basics.
Author: Richard J. Gaylord
Publisher: Springer
Published: 2013-04-17
Total Pages: 315
ISBN-13: 1475711328
DOWNLOAD EBOOKAn Introduction to Programming with Mathematica is the first book published expressly to teach Mathematica as a programming language to scientists, engineers, mathematicians, and computer scientists. This text may be used in a first or second course on programming at the undergraduate level or in a Mathematica-related course in engineering, mathematics, or the sciences. It is also intended for individual study by students and professionals. The text does not assume familiarity with Mathematica nor does it require any prior programming experience. The book and diskette contain over 200 exercises drawn from many areas of science, engineering, mathematics, and computer science. The 3 1/2'' diskette included with this book can be read by UNIX, IBM-compatible, NeXT, and Macintosh computers. The diskette includes Notebooks and packages containing the code for all of the examples and exercises in the text, as well as additional material extending many of the ideas in the text. The packages will run on any computer running Mathematica and the Notebooks will run on any computer that supports Mathematica Notebooks. Version 2.0 or later of Mathematica is recommended for maximum use of the diskette.
Author: Daniel J. Denis
Publisher: John Wiley & Sons
Published: 2021-03-19
Total Pages: 576
ISBN-13: 1119583020
DOWNLOAD EBOOKAN UPDATED GUIDE TO STATISTICAL MODELING TECHNIQUES USED IN THE SOCIAL AND BEHAVIORAL SCIENCES The revised and updated second edition of Applied Univariate, Bivariate, and Multivariate Statistics: Understanding Statistics for Social and Natural Scientists, with Applications in SPSS and R contains an accessible introduction to statistical modeling techniques commonly used in the social and behavioral sciences. The text offers a blend of statistical theory and methodology and reviews both the technical and theoretical aspects of good data analysis. Featuring applied resources at various levels, the book includes statistical techniques using software packages such as R and SPSS®. To promote a more in-depth interpretation of statistical techniques across the sciences, the book surveys some of the technical arguments underlying formulas and equations. The thoroughly updated edition includes new chapters on nonparametric statistics and multidimensional scaling, and expanded coverage of time series models. The second edition has been designed to be more approachable by minimizing theoretical or technical jargon and maximizing conceptual understanding with easy-to-apply software examples. This important text: Offers demonstrations of statistical techniques using software packages such as R and SPSS® Contains examples of hypothetical and real data with statistical analyses Provides historical and philosophical insights into many of the techniques used in modern social science Includes a companion website that includes further instructional details, additional data sets, solutions to selected exercises, and multiple programming options Written for students of social and applied sciences, Applied Univariate, Bivariate, and Multivariate Statistics, Second Edition offers a text to statistical modeling techniques used in social and behavioral sciences.
Author: Peter Mitic
Publisher: World Scientific
Published: 2003
Total Pages: 435
ISBN-13: 1860943632
DOWNLOAD EBOOKThis volume consists of papers delivered at the International Mathematica Symposium 2003 ? an interdisciplinary meeting bringing together users of Mathematica in research and education. It gathers research papers, reports on classroom practice, reports on the use of Mathematica in industry and commerce, and descriptions of fresh applications.List of contributors: J Nash, S Wolfram, R Maeder, B Buchberger and C McTague.
