Parametric statistic is a term used in statistics to refer to a method of inferential data analysis that assumes data is drawn from a population that follows a specific probability distribution. The word "parametric" is pronounced /ˌpærəˈmɛtrɪk/ with stress on the second syllable. The /p/ and /r/ sounds are followed by an unstressed schwa /ə/ sound, and the second syllable contains the two distinct short vowels /ɛ/ and /ɪ/. The unique spelling of this term reflects the specific technical context in which it is used.
Parametric statistics, also known as parametric methods, refer to a class of statistical techniques used to analyze data based on specific assumptions about the population from which the data is drawn. These assumptions usually involve characteristics such as the shape of the data distribution, the variability of the data, and the relationship between variables.
Parametric statistics rely on the use of mathematical models to describe the data, making inferences about the population parameters based on sample statistics. These statistical models often specify the probability distribution of the variables being analyzed and involve estimating unknown parameters, such as means or variances.
One fundamental assumption of parametric statistics is that the data under investigation are drawn from a specific population with a known distribution. For example, the assumption of normality is commonly used in parametric statistics, where it is assumed that the data is normally distributed.
Parametric statistics encompass a wide range of techniques, including hypothesis testing, confidence interval estimation, regression analysis, analysis of variance (ANOVA), and many others. These techniques are widely used in statistical research and applied areas such as social sciences, business, and engineering.
In summary, parametric statistics are a set of techniques used to analyze data assuming specific population distributions and estimating population parameters. These methods are based on mathematical models and play a crucial role in making statistical inferences and drawing conclusions from sample data.
The word "parametric" in the context of statistics is derived from the Greek words "para" meaning "beside" or "beyond", and "metron" meaning "measure" or "rule". Therefore, "parametric" refers to measurements or rules that go beyond what is directly observed or measured. In statistics, parametric methods assume that the data follows a specific distribution or model and involve estimating the parameters of that distribution or model to make inferences or draw conclusions.
The word "statistic" is derived from the Latin word "statisticum" meaning "state affairs" or "political science". It was originally used in the context of analyzing data related to populations and societies. Over time, "statistic" evolved to refer to numerical measures used to describe or summarize data in various scientific disciplines, including statistics.