Statistical data analysis explained : applied environmental...

Main
Mathematics
Statistical data analysis explained :...

Statistical data analysis explained : applied environmental statistics with R

Clemens Reimann, Peter Filzmoser, Robert Garrett, Rudolf Dutter

5.0 / 5.0

Насколько вам понравилась эта книга?

Какого качества скаченный файл?

Скачайте книгу, чтобы оценить ее качество

Какого качества скаченные файлы?

Категории:

Год:

2008

Издательство:

Wiley

Язык:

english

Страницы:

359

ISBN 10:

047098581X

ISBN 13:

9780470985816

Файл:

PDF, 14.69 MB

IPFS:

,

english, 2008

Читать Онлайн

Скачать (pdf, 14.69 MB)

Выполняется конвертация в

Конвертация в не удалась

Вас может заинтересовать

Mike McGrath — R for Data Analysis in easy steps: R Programming Essentials

Andrew Oleksy — Data Science with R A Step By Step Guide With Visual Illustrations and Examples

Vamsee Puligadda — 500 Data Science Interview Questions and Answers

Norman S. Matloff — Probability and Statistics for Data Science: Math + R + Data

Larry Wasserman — All of Statistics: A Concise Course in Statistical Inference

Jonathan D. Cryer, Kung-Sik Chan — Time Series Analysis: With Applications in R

Peter Dalgaard — Introductory Statistics With R (Second Edition)

Maria L. Rizzo — Statistical computing with R

Richard Webster, Margaret A. Oliver — Geostatistics for Environmental Scientists

Brian S. Everitt, Dr Sabine Landau, Dr Morven Leese, Dr Daniel Stahl — Cluster Analysis, Fifth Edition (Wiley Series in Probability and Statistics)

Nathan Yau — Visualize This: The Flowing Data Guide to Design, Visualization, and Statistics

Suhov Y., Kelbert M. — Probability and statistics by example. Basic probability and statistics

D. R. Cox — Principles of Statistical Inference

Andrew Gelman, Jennifer Hill — Data Analysis Using Regression and Multilevel/Hierarchical Models

Robert S. Witte, John S. Witte — Statistics

Marc S. Paolella — Linear Models and Time-Series Analysis: Regression, ANOVA, ARMA and GARCH

Daniel J. Denis — Univariate, Bivariate, and Multivariate Statistics Using R: Quantitative Tools for Data Analysis and Data Science

Dieter Rasch Rostock, Rob Verdooren Wageningen, Jürgen Pilz Klagenfurt — Applied Statistics: Theory and Problem Solutions with R

Mohiuddin Ahmed, Al-Sakib Khan Pathan — Data Analytics: Concepts, Techniques, and Applications

S. Christian Albright, Wayne L. Winston — Business Analytics: Data Analysis & Decision Making

Brian S. Everitt, Torsten Hothorn — A handbook of statistical analyses using R

Andy Field, Jeremy Miles, Zoë Field — Discovering Statistics Using R

Garrett Grolemund, Hadley Wickham — Hands-On Programming with R: Write Your Own Functions and Simulations

Matthew B. Miles, A. Michael Huberman, Johnny Saldaña — Qualitative Data Analysis: A Methods Sourcebook

Hadley Wickham. — Advanced R

Nicholas J. Horton, Ken Kleinman — Using R and RStudio for Data Management, Statistical Analysis and Graphics

James O. Aldrich, James B. Cunningham — Using IBM® SPSS® Statistics: An Interactive Hands-On Approach

N.D. Lewis — 100 Statistical Tests: In R

Allen B. Downey — Think Stats: Exploratory Data Analysis (Second Edition)

Hadley Wickham — R Packages: Organize, Test, Document, and Share Your Code

Peter Bruce, Andrew Bruce — Practical Statistics for Data Scientist

Jd Long; Paul Teetor — R Cookbook: Proven Recipes for Data Analysis, Statistics, and Graphics

Aileen Nielsen — Practical Time Series Analysis: Prediction with Statistics and Machine Learning

Song S. Qian — Environmental and Ecological Statistics with R, Second Edition

Lisa Daniels, Nicholas Minot — An Introduction to Statistics and Data Analysis Using Stata®

David Borman — Statistics 101: From Data Analysis and Predictive Modeling to Measuring Distribution and Determining Probability, Your Essential Guide to Statistics (Adams 101)

John Fox, Sanford Weisberg — An R Companion to Applied Regression

Robert Kabacoff — R in Action: Data Analysis and Graphics with R, Second Edition

Nina Zumel, John Mount — Practical Data Science with R

Andrea Cirillo — RStudio for R Statistical Computing Cookbook: Over 50 practical and useful recipes to help you perform data analysis with R by unleashing every native RStudio feature

Arshdeep Bahga, Vijay Madisetti — Big Data Analytics: A Hands-On Approach

Frank E. Harrell , Jr. (auth.) — Regression Modeling Strategies: With Applications to Linear Models, Logistic and Ordinal Regression, and Survival Analysis

Ключевые слова

Связанные Подборки