Statistical Analysis and Machine Learning

Topics in Fundemantal Statistics

P-values, Confidence Intervals and Effect size

In this section I write about misinterpretation of basic but widely used statistical concepts. P-values, confidence intervals and other inferential and summary statistics are important for a robust statistical analysis, and reaching sound conclusions, but are elements that have been abused by researchers and practitioners alike.

Supervised Learning

Linear Regression

Sources:

1. The Elements of Statistical Learning
2. An Introduction to Statistical Learning: With Applications in R

Folder: Regression Methods

Similarly to almost any statistical model, linear regression assumes a matrix of inputs $X$ with $X \in \mathbb{R}^{n \times d}$, $n$ being the number of observations and $d$ being the number of dimensions in the dataset.

As an example