Tilastot

Tilastot, or statistics, is the discipline that deals with collecting, organizing, analyzing, interpreting and presenting data to describe and infer properties of populations or processes. It covers descriptive statistics, which summarize data from a sample or population, and inferential statistics, which use probability theory to draw broader conclusions from observed data.

Data are gathered through methods such as censuses, surveys, experiments and administrative records. Data types include quantitative data (discrete or continuous) and qualitative data (nominal or ordinal), measured on different scales. A core activity is designing studies that yield reliable evidence, including sampling plans and experimental designs.

Analytical tools include measures of central tendency and dispersion, visualizations such as histograms and scatter plots, and models from probability and statistics. Descriptive statistics summarize current data; inferential statistics allow estimation, hypothesis testing, confidence intervals, and prediction. Methods such as regression, correlation, and Bayesian inference help relate variables and quantify uncertainty.

Statistics is applied across fields: government policy, medicine and public health, business and finance, quality control, ecology, psychology, sports analytics and more. It also raises ethical concerns about privacy, bias, and reproducibility of results.

Historically, statistics has roots in state record-keeping and demography. The field was advanced by figures such as Adolphe Quetelet, Carl Friedrich Gauss, Karl Pearson and Ronald Fisher. Today it underpins data-driven decision making and is closely linked to data science.

In Finnish, tilastot means statistics, and many countries have national statistical offices (for example, Statistics Finland, or Tilastokeskus, the Finnish agency).