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

Random Walk simulation


Random Walk is a simulation where a succession of random steps are used to represent an apparently random event. The interesting thing is that we can use this kind of simulation to see different outputs from a certain event by controlling the start point of the simulation and the probability distribution of the random steps. Like all simulations, this is just a simplified model of the original phenomena. However, a simulation might be useful and is a powerful visualization tool. There are different notions of Random Walks using different implementations, with the most common being Brownian motion and the Binomial model. We will use these models to visualize the random path followed by stock prices through time.

In the following diagram, we can see simulated data from the Random Walk model for logged stock prices:

Brownian motion is a Random Walk model named after physicist Robert Brown, who observed molecules moving and colliding with one another in a random fashion...