The following outline is provided as an overview of and topical guide to statistics:
Statistics is a field of inquiry that studies the collection, analysis, interpretation, and presentation of data. It is applicable to a wide variety of academic disciplines, from the physical and social sciences to the humanities; it is also used and misused for making informed decisions in all areas of business and government.
Nature of statistics
editStatistics can be described as all of the following:
- An academic discipline: one with academic departments, curricula and degrees; national and international societies; and specialized journals.
- A scientific field (a branch of science) – widely recognized category of specialized expertise within science, and typically embodies its own terminology and nomenclature. Such a field will usually be represented by one or more scientific journals, where peer reviewed research is published.
- A formal science – branch of knowledge concerned with formal systems.
- A mathematical science – field of science that is primarily mathematical in nature but may not be universally considered subfields of mathematics proper. Statistics, for example, is mathematical in its methods but grew out of political arithmetic which merged with inverse probability and grew through applications in the social sciences and some areas of physics and biometrics to become its own separate, though closely allied, field.
History of statistics
editDescribing data
editExperiments and surveys
editSampling
editAnalysing data
editFiltering data
editStatistical inference
editProbability distributions
editRandom variables
editProbability theory
editComputational statistics
edit- Computational statistics
- Markov chain Monte Carlo
- Bootstrapping (statistics)
- Jackknife resampling
- Integrated nested Laplace approximations
- Nested sampling algorithm
- Metropolis–Hastings algorithm
- Importance sampling
- Mathematical optimization
- Convex optimization
- Linear programming
- Linear matrix inequality
- Quadratic programming
- Quadratically constrained quadratic program
- Second-order cone programming
- Semidefinite programming
- Newton-Raphson
- Gradient descent
- Conjugate gradient method
- Mirror descent
- Proximal gradient method
- Geometric programming