statisticsused

Statistics used refers to the collection of statistical methods and measures applied to data to summarize, analyze, and interpret information. It encompasses the planning, execution, and reporting of quantitative analysis across scientific, business, and public sectors.

Common statistics used include descriptive statistics such as mean, median, mode, range, and standard deviation, which summarize data; inferential statistics like confidence intervals, hypothesis tests, and p-values, used to generalize findings from samples to populations; and regression and correlation analyses to assess relationships between variables. It also includes multivariate methods such as principal component analysis, cluster analysis, and factor analysis, as well as time-series methods for ordered data, Bayesian approaches for probabilistic modeling, and nonparametric techniques when assumptions are mild or violated.

Choosing statistics used depends on data type (numerical versus categorical), sample size, measurement error, distributional assumptions, and the analysis goal (estimation, testing, prediction). The workflow typically involves data cleaning, exploratory data analysis, model selection, validation, and reporting with quantified uncertainty.

Limitations and challenges include bias in sampling, measurement error, overfitting, misinterpretation of p-values, and selective reporting. Good practice emphasizes transparency, preregistration when possible, reproducible code, and clear communication of assumptions and limitations.

See also: Statistics, Data analysis, Experimental design, Data science, Reproducibility in research.