Probability & Statistical Inference · Statistical Inference & Estimation

Statistical Inference: Introduction and General Principles

Public introduction · full guide in Eikos

Introduction

What this guide covers

From the observable sample to the unobservable population: the art and science of reasoning under uncertainty with mathematical rigor.

Overview

Topics covered

  • Introduction
  • Introduction and General Principles
  • Introduction to Statistical Inference
  • The Inferential Paradigm
  • Historical Note
  • Population, Sample and Statistical Model

Related concepts

Main connections

  • Maximum likelihood estimation
  • Variance & standard deviation
  • Bayes' theorem & priors
  • Mean & expected value
  • Confidence interval
  • Median & robust location

Compatible notation

Mathematical sample in LaTeX

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

θ∈Θ⏟Parameter desconocido→genera(X1,…,Xn)∼Fθ⊗n⏟Sample aleatoria→inferenciaθ^(𝐗),C(𝐗),ϕ(𝐗)⏟Estimator, IC, test
View LaTeX source\underbrace{\theta \in \Theta}_{\text{Parameter desconocido}} \xrightarrow{\text{genera}} \underbrace{(X_1, \ldots, X_n) \sim F_\theta^{\otimes n}}_{\text{Sample aleatoria}} \xrightarrow{\text{inferencia}} \underbrace{\hat{\theta}(\mathbf{X}), \; C(\mathbf{X}), \; \phi(\mathbf{X})}_{\text{Estimator, IC, test}}