Statistica

Statistica is the branch of science that concerns the collection, organization, analysis, interpretation and presentation of data. It provides methods to describe data sets, to infer properties of larger populations from samples, and to quantify uncertainty. Core components include descriptive statistics for summarizing data, and inferential statistics for drawing conclusions, along with probability theory that underpins modeling and uncertainty.

Historically, statistical ideas emerged from early demographic and probabilistic work in the 17th to 19th centuries and were formalized in the 20th century with the development of sampling theory, experimental design, and statistical inference. Key figures include John Graunt, Adolphe Quetelet, Karl Pearson, Ronald Fisher, Jerzy Neyman and Egon Pearson. Over time statistics expanded into many disciplines, giving rise to subfields such as biostatistics, econometrics, psychometrics, and data science.

Methods and practices in statistics include planning data collection, sampling, measurement, and data cleaning, followed by exploratory data analysis; then modeling and inference using techniques such as hypothesis testing, estimation, confidence intervals, regression, analysis of variance, time series and multivariate methods. Bayesian approaches provide an alternative framework for probabilistic reasoning that complements classical (frequentist) methods.

Applications of statistics span science, engineering, medicine, public policy, economics, business, sports, and the social sciences. They support evidence-based decision making, risk assessment, and forecasting.

In recent decades statistics has evolved alongside computing and data science, with emphasis on large and complex data, algorithmic modeling, reproducibility, and ethical considerations in data collection and analysis.