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Numerical Computing with Python: Harness the power of Python to analyze and find hidden patterns in the data
Numerical Computing with Python: Harness the power of Python to analyze and find hidden patterns in the data

Understand, explore, and effectively present data using the powerful data visualization techniques of Python

Key Features

  • Use the power of Pandas and Matplotlib to easily solve data mining issues
  • Understand the basics of statistics to build powerful predictive data...
Schaum's Outline of Mathematica, 2ed (Schaum's Outline Series)
Schaum's Outline of Mathematica, 2ed (Schaum's Outline Series)
Master Mathematica with Schaum's, the high-performance study guide. It will help you cut study time, hone problem-solving skills, and achieve your personal best on exams and projects!

Students love Schaum's Outlines because they produce results. Each year, hundreds of thousands of students improve their test scores and final grades with these...

Data Analysis Using SAS Enterprise Guide
Data Analysis Using SAS Enterprise Guide

The present book, Data Analysis Using SAS Enterprise Guide, provides readers with an overview of Enterprise Guide, the newest point-and-click interface from SAS. SAS Enterprise Guide is a graphical user (point-and-click) interface to the main SAS application, having relatively recently replaced the Analyst interface, which itself had replaced...

S+Functional Data Analysis User's Guide
S+Functional Data Analysis User's Guide
S+Functional Data Analysis is the first commercial object oriented package for exploring, modeling, and analyzing functional data. Functional data analysis (FDA) handles longitudinal data and treats each observation as a function of time (or other variable). The functions are related. The goal is to analyze a sample of functions instead of a...
Meta-Learning in Computational Intelligence (Studies in Computational Intelligence)
Meta-Learning in Computational Intelligence (Studies in Computational Intelligence)

In the early days of pattern recognition and statistical data analysis life was rather simple: datasets were relatively small, collected from well-designed experiments, analyzed using a few methods that had good theoretical background. Explosive growth of the use of computers led to the creation of huge amounts of data of all kinds,...

Statistical Methods in Analytical Chemistry (Chemical Analysis: A Series of Monographs on Analytical Chemistry and Its Applications)
Statistical Methods in Analytical Chemistry (Chemical Analysis: A Series of Monographs on Analytical Chemistry and Its Applications)

This new edition of a successful, bestselling book continues to provide you with practical information on the use of statistical methods for solving real-world problems in complex industrial environments. Complete with examples from the chemical and pharmaceutical laboratory and manufacturing areas, this thoroughly updated book clearly...

Risk and Portfolio Analysis: Principles and Methods (Springer Series in Operations Research and Financial Engineering)
Risk and Portfolio Analysis: Principles and Methods (Springer Series in Operations Research and Financial Engineering)

Investment and risk management problems are fundamental problems for  financial institutions and involve both speculative and hedging decisions. A structured approach to these problems naturally leads one to the field of applied mathematics in order to translate subjective probability beliefs and attitudes towards risk and reward into...

Minitab Cookbook
Minitab Cookbook

With over 110 practical recipes, this is the ideal book for all statisticians who want to explore the vast capabilities of Minitab to organize data, analyze it, and visualize it with impactful graphs.

Overview

  • Gain an in-depth understanding of data formatting in Minitab
  • Understand the steps...
Robust Statistics: Theory and Methods (Probability and Statistics)
Robust Statistics: Theory and Methods (Probability and Statistics)
Classical statistical techniques fail to cope well with deviations from a standard distribution. Robust statistical methods take into account these deviations while estimating the parameters of parametric models, thus increasing the accuracy of the inference. Research into robust methods is flourishing, with new methods being developed and...
The R Book
The R Book

R is a high-level language and an environment for data analysis and graphics. The design of R was heavily influenced by two existing languages: Becker, Chambers and Wilks’ S and Sussman’s Scheme. The resulting language is very similar in appearance to S, but the underlying implementation and semantics are derived from Scheme. This...

A Matrix Handbook for Statisticians (Wiley Series in Probability and Statistics)
A Matrix Handbook for Statisticians (Wiley Series in Probability and Statistics)
A comprehensive, must-have handbook of matrix methods with a unique emphasis on statistical applications

This timely book, A Matrix Handbook for Statisticians, provides a comprehensive, encyclopedic treatment of matrices as they relate to both statistical concepts and methodologies. Written by an experienced authority on matrices and...

Between the Lines of Genetic Code: Genetic Interactions in Understanding Disease and Complex Phenotypes
Between the Lines of Genetic Code: Genetic Interactions in Understanding Disease and Complex Phenotypes

Between the Lines of Genetic Code lays out methodologies and tools for the measurement and evaluation of gene-gene and gene-environment studies and gives perspective on the future of this discipline. The book begins by defining terms for interaction studies, describing methodologies, and critically assessing the viability of current...

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