Читать книгу Applied Biostatistics for the Health Sciences - Richard J. Rossi - Страница 19

In developing the statistical protocol to be used in a research study, biostatisticians use the basic terminology listed below.

 The target population is the population that is being studied in the research project.

 The units of a target population are the objects on which the measurements will be taken. When the units of the population are human beings, they are referred to as subjects or individuals.

 A subpopulation of the target population is a well-defined subset of the population units.

 A parameter is a numerical measure of a characteristic of the target population.

 A sample is a subset of the target population units. A census is sample consisting of the entire set of population units.

 The sample size is the number of units observed in the sample.

 A random sample is a sample that is chosen according to a sampling plan where the probability of each possible sample that can be drawn from the target population is known.

 A statistic is any value that is computed using only the sample observations and known values.

 A cohort is a group of subjects having similar characteristics.

 A variable is a characteristic that will be recorded or measured on a unit in the target population.

 A response variable or outcome variable is the variable in a research study that is of primary interest or the variable that is being modeled. The response variable is also sometimes called the dependent variable.

 An explanatory variable is a variable that is used to explain or is believed to cause changes in the response variable. The explanatory variables are also called independent variables or predictor variables.

 A treatment is any experimental condition that is applied to the units.

 A placebo is an inert or inactive treatment that is applied to the units.

 A statistical inference is an estimate, conclusion, or generalization made about the target population from the information contained in an observed sample.

 A statistical model is a mathematical formula that relates the response variable to the explanatory variables.

One of the most misunderstood and abused concepts in statistics is the difference between a parameter and a statistic, and researchers who do not have a basic understanding of statistics often use these terms interchangeably, which is incorrect. Whether a number is a parameter or a statistic is determined by asking whether or not the number was computed from the entire set of units in the target population (parameter) or from a sample of the units in the target population (statistic). It is important to distinguish whether a number is a parameter or a statistic because a parameter will provide the answer to a statistical research question, while a statistic can provide information only regarding the answer, and there is a degree of uncertainty associated with the information contained in a statistic.