Data di Pubblicazione:
2018
Abstract:
Hypothesis testing is a statistical decisional process that allows one to choose between two complementary possibilities on the basis of samples drawn from the population(s) of interest. The two possibilities are called the null and alternative hypothesis, respectively. For each decision, two types of errors might occur, i.e., rejecting the null hypothesis when it is true (Type I error) or accepting the null hypothesis when it is false (Type II error). The decision is taken by compromising the two error types. When multiple hypotheses are compared one also has to define and control the overall decisional error.
Tipologia CRIS:
02.01 Contributo in volume (Capitolo o Saggio)
Keywords:
Test Statistics; False Discovery Rate; Type I error; Type II error; Multiple Testing; P-value
Elenco autori:
Angelini, Claudia
Link alla scheda completa:
Titolo del libro:
Volume 1 - Methods