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 Statistics 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 History of statistics Founders of statistics History of probability Timeline of probability and statistics Describing data Descriptive statistics Average Mean Median Mode Measures of scale Variance Standard deviation Median absolute deviation Correlation Polychoric correlation Outlier Statistical graphics Histogram Frequency distribution Quantile Survival function Failure rate Scatter plot Bar chart Experiments and surveys Design of experiments Optimal design Factorial experiment Restricted randomization Repeated measures design Randomized block design Cross-over design Randomization Statistical survey Opinion poll Sampling Sampling theory Sampling distribution Stratified sampling Quota sampling Cluster sampling Biased sample Spectrum bias Survivorship bias Analysing data Regression analysis Outline of regression analysis Analysis of variance (ANOVA) General linear model Generalized linear model Generalized least squares Mixed model Elastic net regularization Ridge regression Lasso (statistics) Survival analysis Density estimation Kernel density estimation Multivariate kernel density estimation Time series Time series analysis Box–Jenkins method Frequency domain Time domain Multivariate analysis Principal component analysis (PCA) Factor analysis Cluster analysis Multiple correspondence analysis Nonlinear dimensionality reduction Robust statistics Heteroskedasticity-consistent standard errors Newey–West estimator Generalized estimating equation Bootstrapping (statistics) Statistical classification Metric learning Generative model Discriminative model Online machine learning Cross-validation (statistics) Filtering data Recursive Bayesian estimation Kalman filter Particle filter Moving average SQL