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Mathematica Data Analysis
Table of Contents
Mathematica Data Analysis
Credits
About the Author
About the Reviewer
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Preface
What this book covers
What you need for this book
Who this book is for
Conventions
Reader feedback
Customer support
Downloading the example code
Errata
Piracy
Questions
1. First Steps in Data Analysis
System installation
Setting up the system
The Mathematica front end and kernel
Main features for writing expressions
Summary
2. Broad Capabilities for Data Import
Permissible data format for import
Importing data in Mathematica
Additional cleaning functions and data conversion
Checkpoint 2.1 – time for some practice!!!
Importing strings
Importing data from Mathematica's notebooks
Controlling data completeness
Summary
3. Creating an Interface for an External Program
Wolfram Symbolic Transfer Protocol
Interface implementation with a program in С/С++
Calling Mathematica from C
Interacting with .NET programs
Interacting with Java
Interacting with R
Summary
4. Analyzing Data with the Help of Mathematica
Data clustering
Data classification
Image recognition
Recognizing faces
Recognizing text information
Recognizing barcodes
Summary
5. Discovering the Advanced Capabilities of Time Series
Time series in Mathematica
Mathematica's information depository
Process models of time series
The moving average model
The autoregressive process – AR
The autoregression model – moving average (ARMA)
The seasonal integrated autoregressive moving-average process – SARIMA
Choosing the best time series process model
Tests on stationarity, invertibility, and autocorrelation
Checking for stationarity
Invertibility check
Autocorrelation check
Summary
6. Statistical Hypothesis Testing in Two Clicks
Hypotheses about the mean
Hypotheses about the variance
Checking the degree of sample dependence
Hypotheses on true sample distribution
Summary
7. Predicting the Dataset Behavior
Classical predicting
Image processing
Probability automaton modelling
Summary
8. Rock-Paper-Scissors – Intelligent Processing of Datasets
Interface development in Mathematica
Markov chains
Creating a portable demonstration
Summary
Index
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