Probability & Statistical Inference · Descriptive Statistics & EDA

Descriptive statistics: Computational implementation and practical aspects

Public introduction · full guide in Eikos

Introduction

What this guide covers

Introduction X_cent <- X |> mutate(x = x - mean(x)) |> summarise(cov = sum(x * y) / (n() - 1)) Rigorous Mathematical Treatment

Overview

Topics covered

  • Introduction
  • Descriptive Statistics Computational and Practical Implementation
  • Epistemology of Measurement and Data Representation
  • Stevens Scales and Measurement Homomorphisms
  • Data Structuring: Design Matrices and Tensors
  • Centrality Measures: Theory, Algorithms and Stability

Related concepts

Main connections

  • Skewness & kurtosis
  • Quantiles & percentiles
  • Mean & expected value
  • Variance & standard deviation
  • Median & robust location
  • Outliers & influence diagnostics

Compatible notation

Mathematical sample in LaTeX

The expression is rendered accessibly, with its LaTeX source preserved below.

(a1,a2,…,am)∈Ri⟺(f(a1),f(a2),…,f(am))∈Si
View LaTeX source\left( a_1, a_2, \ldots, a_m \right) \in R_i \iff \left( f(a_1), f(a_2), \ldots, f(a_m) \right) \in S_i