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
