Statistics, Linear Regression, and Randomness
Jason Bell · Machine Learning · 2020
This chapter discusses some statistical concepts and how they can be used, and covers datasets, standard deviation, Bayesian techniques, forms of linear regression, and the power of random numbers. The code to accompany the chapter will be in both Java and Clojure. The chapter shows how to load data with Java and Clojure. Statistics are straightforward enough in code. The chapter also discusses basic summary statistics: the sum, minimum and maximum, mean, mode, median, range, variance, and standard deviation, as well as Java and Clojure variations. While linear regression is not a machine learning algorithm, it is classed as a statistical method. Simple linear regression plots an independent variable (the predictor) against a dependent variable (criterion variable). Finally, the chapter looks at two aspects of using random numbers: finding Pi using some basic math and Monte Carlo methods; and random walks.