#### Overview of this book

There are many algorithms for data analysis and it’s not always possible to quickly choose the best one for each case. Implementation of the algorithms takes a lot of time. With the help of Mathematica, you can quickly get a result from the use of a particular method, because this system contains almost all the known algorithms for data analysis. If you are not a programmer but you need to analyze data, this book will show you the capabilities of Mathematica when just few strings of intelligible code help to solve huge tasks from statistical issues to pattern recognition. If you're a programmer, with the help of this book, you will learn how to use the library of algorithms implemented in Mathematica in your programs, as well as how to write algorithm testing procedure. With each chapter, you'll be more immersed in the special world of Mathematica. Along with intuitive queries for data processing, we will highlight the nuances and features of this system, allowing you to build effective analysis systems. With the help of this book, you will learn how to optimize the computations by combining your libraries with the Mathematica kernel.
Mathematica Data Analysis
Credits
www.PacktPub.com
Preface
Free Chapter
First Steps in Data Analysis
Creating an Interface for an External Program
Analyzing Data with the Help of Mathematica
Discovering the Advanced Capabilities of Time Series
Statistical Hypothesis Testing in Two Clicks
Predicting the Dataset Behavior
Rock-Paper-Scissors – Intelligent Processing of Datasets
Index

## Chapter 7. Predicting the Dataset Behavior

Analyzing data is important to identify and understand inner dependencies. By examining the exchange rates statistics, we can trace how they grow or fall depending on the political, economic, psychological, and even informational events. These dependencies will subsequently help to determine the future rate value in case of repeated factors influence. So, data analysis often comes down to learning how to make predictions. However, you can predict not just numerical data. Mathematica has gone beyond the number fields long ago and handles audio, video, and text information as easily as numbers.

From this chapter, you will obtain the necessary knowledge to learn how to predict with Mathematica, such as the following:

• Predicting the future values of sampling data

• Intelligent picture processing and replicating style patterns

• Predicting with the help of probability automaton model