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Chemometrics with R: Multivariate Data Analysis in the Natural Sciences and Life Sciences (Use R!)
Chemometrics with R: Multivariate Data Analysis in the Natural Sciences and Life Sciences (Use R!)

This accessible primer on multivariate statistics in the life sciences gives a full description of the general data analysis paradigm, from exploratory analysis to modeling to validation; covers other aspects of chemometrics; and supplies the relevant R code.

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An R and S-Plus® Companion to Multivariate Analysis (Springer Texts in Statistics)
An R and S-Plus® Companion to Multivariate Analysis (Springer Texts in Statistics)

Applied statisticians often need to perform analyses of multivariate data; for these they will typically use one of the statistical software packages, S-Plus or R. This book sets out how to use these packages for these analyses in a concise and easy-to-use way, and will save users having to buy two books for the job. The author is...

Always Be Testing: The Complete Guide to Google Website Optimizer
Always Be Testing: The Complete Guide to Google Website Optimizer
Stop guessing, start testing, and enjoy greater success with your website.

If you’re looking for more leads, sales, and profit from your website, then look no further than this expert guide to Google’s free A/B and multivariate website testing tool, Google Website Optimizer. Recognized online marketing guru and New York...

Smoothing Spline ANOVA Models (Springer Series in Statistics)
Smoothing Spline ANOVA Models (Springer Series in Statistics)

Nonparametric function estimation with stochastic data, otherwise known as smoothing, has been studied by several generations of statisticians. Assisted by the ample computing power in today's servers, desktops, and laptops, smoothing methods have been finding their ways into everyday data analysis by practitioners. While scores of...

Introduction to Machine Learning (Adaptive Computation and Machine Learning)
Introduction to Machine Learning (Adaptive Computation and Machine Learning)
The goal of machine learning is to program computers to use example data or past experience to solve a given problem. Many successful applications of machine learning exist already, including systems that analyze past sales data to predict customer behavior, recognize faces or spoken speech, optimize robot behavior so that a task can be completed...
Introduction to Data Mining and its Applications (Studies in Computational Intelligence)
Introduction to Data Mining and its Applications (Studies in Computational Intelligence)
An enormous proliferation of databases in almost every area of human endeavor has created a great demand for new, powerful tools for turning data into useful, task-oriented knowledge. In the efforts to satisfy this need, researchers have been exploring ideas and methods developed in machine learning, pattern recognition, statistical data analysis,...
Nonlinear Biomedical Signal Processing, Fuzzy Logic, Neural Networks, and New Algorithms (IEEE Press Series on Biomedical Engineering) (Volume 1)
Nonlinear Biomedical Signal Processing, Fuzzy Logic, Neural Networks, and New Algorithms (IEEE Press Series on Biomedical Engineering) (Volume 1)

For the first time, eleven experts in the fields of signal processing and biomedical engineering have contributed to an edition on the newest theories and applications of fuzzy logic, neural networks, and algorithms in biomedicine. Nonlinear Biomedical Signal Processing, Volume I provides comprehensive coverage of nonlinear signal...

SAS/STAT 9.1 User's Guide, Volumes 1-7
SAS/STAT 9.1 User's Guide, Volumes 1-7
SAS/STAT software provides extensive statistical capabilities with tools for both specialized and enterprise-wide analytical needs. It can help you analyze data and make informed decisions for research, engineering, manufacturing, medical, and business applications. This user's guide provides the latest, detailed reference material for the...
Multivariate Time Series Analysis: With R and Financial Applications
Multivariate Time Series Analysis: With R and Financial Applications

An accessible guide to the multivariate time series tools used in numerous real-world applications

Multivariate Time Series Analysis: With R and Financial Applications is the much anticipated sequel coming from one of the most influential and prominent experts on the topic of time series. Through a...

Lattice: Multivariate Data Visualization with R (Use R)
Lattice: Multivariate Data Visualization with R (Use R)
R is rapidly growing in popularity as the environment of choice for data analysis and graphics both in academia and industry. Lattice brings the proven design of Trellis graphics (originally developed for S by William S. Cleveland and colleagues at Bell Labs) to R, considerably expanding its capabilities in the process. Lattice is a powerful and...
SAS(R) Add-In 2.1 for Microsoft Office: Getting Started with Data Analysis
SAS(R) Add-In 2.1 for Microsoft Office: Getting Started with Data Analysis
Provides step-by-step instructions for analyzing data in Microsoft Excel. You will be guided through several SAS tasks and shown how you can harness the power of SAS in Microsoft Excel. The scenarios in the book use sample data that is provided with Base SAS software, so you can follow the instructions to perform this analysis.

The SAS
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Statistical Analysis of Management Data
Statistical Analysis of Management Data

Statistical Analysis of Management Data provides a comprehensive approach to multivariate statistical analyses that are important for researchers in all fields of management, including finance, production, accounting, marketing, strategy, technology, and human resources. This book is especially designed to provide doctoral students...

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