Book Image

Haskell Data Analysis cookbook

By : Nishant Shukla
Book Image

Haskell Data Analysis cookbook

By: Nishant Shukla

Overview of this book

Step-by-step recipes filled with practical code samples and engaging examples demonstrate Haskell in practice, and then the concepts behind the code. This book shows functional developers and analysts how to leverage their existing knowledge of Haskell specifically for high-quality data analysis. A good understanding of data sets and functional programming is assumed.
Table of Contents (14 chapters)
13
Index

Chapter 7. Statistics and Analysis

One core motivation to analyze big data is to find intrinsic patterns. This chapter contains recipes that answer questions about data deviation from the norm, existence of linear and quadratic trends, and probabilistic values of a network. Some of the most fascinating results can be uncovered by the following recipes:

  • Calculating a moving average
  • Calculating a moving median
  • Approximating a linear regression
  • Approximating a quadratic regression
  • Obtaining the covariance matrix from samples
  • Finding all unique pairings in a list
  • Using the Pearson correlation coefficient
  • Evaluating a Bayesian network
  • Creating a data structure for playing cards
  • Using a Markov chain to generate text
  • Creating n-grams from a list
  • Constructing a neural network perception