Probability theory and mathematical statistics emerged in the middle of the 17th century due to the development of society and commodity-money relations. The first who successfully combined anthropology and social statistics methods with the achievements of probability theory and mathematical statistics was the Belgian statistician L. Kettle. It followed from his works that statistics is not just collecting and classifying data but analyzing it to find regularities. L. Kettle was one of the first to show that the randomness observed in living nature, due to its repetitiveness, reveals a definite tendency, which can be described in the language of mathematics.
The term “regression” was introduced by F. Galton in 1886. Galton discovered that, on average, the sons of tall fathers were not as tall, and the sons of small stature were taller than their fathers. He interpreted this as a “regression to mediocrity.” This allowed not only to structure the data but also to delve into the study of disease behavior at different stages of treatment.
In medicine, the advantages of the approach of using mathematical statistics were not immediately apparent. The active adoption of statistics began when the theory of small samples was substantiated. Later, Student developed tables that could be used to determine confidence intervals and check significance criteria based on small pieces, which makes it possible to solve many statistical problems in clinical research. The theory of small samples has received further development in the works of R. Fisher (1890-1962), the whole place in its position occupied with questions of planning of the experiment. Fisher introduced several new terms and concepts into biometry and examined the fundamental principles of statistical inference. He also showed that the planning of experiments and the processing of their results are two inseparable tasks of statistics.
