Book Image

Practical Data Analysis - Second Edition

By : Hector Cuesta, Dr. Sampath Kumar
Book Image

Practical Data Analysis - Second Edition

By: Hector Cuesta, Dr. Sampath Kumar

Overview of this book

Beyond buzzwords like Big Data or Data Science, there are a great opportunities to innovate in many businesses using data analysis to get data-driven products. Data analysis involves asking many questions about data in order to discover insights and generate value for a product or a service. This book explains the basic data algorithms without the theoretical jargon, and you’ll get hands-on turning data into insights using machine learning techniques. We will perform data-driven innovation processing for several types of data such as text, Images, social network graphs, documents, and time series, showing you how to implement large data processing with MongoDB and Apache Spark.
Table of Contents (21 chapters)
Practical Data Analysis - Second Edition
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface

Monte Carlo methods


Random Walk is a member of a family of random sampling algorithms. Proposed by Stanislaw Ulam in 1940, Monte Carlo methods are mainly used when the event has uncertainty and deterministic boundaries (the previous estimate was for a range of limit values). These methods are especially good for optimization and numerical integration in finance, biology, business, physics, and statistics.

Monte Carlo methods depend on the probability distribution of the random number generator to see different behaviors in the simulations. The most common distribution is the Gauss or Normal; this distribution is also referred to as Bell Curve (see the following diagram), but there are more distributions such as the Geometric or Poisson. In statistics, the Central Limit Theorem (CTL) proposes that the Gaussian distribution will appear in almost any case. Where the sample of n elements from a uniform random source (if the number of samples gets larger, the approximation improves), the sum of...