Statistical variable
In the statistical and empirical one assigns statistical variable or a statistical characteristic of a survey unit ( examination unit ) an expression to.
A statistical variable is present if the characteristics of certain characteristics can be expressed by a number or by number intervals (values of the variables ) and these values include empirically measurable frequencies .
Systematics
Population ( population )
- Feature carrier ( investigation unit , survey unit )
- Characteristic ( statistical variable )
- Characteristic value ( value of the variable)
Examples:
- Population : residents of city X
- Characteristic carrier: a resident
- Feature: gender
- Characteristic expression: male
- Population: days of a study period
- Characteristic carrier: one day
- Feature: amount of precipitation in Germany
- Characteristic expression: 1.5 cubic kilometers
Classification of features
Features can have different scale levels . In principle, a distinction can be made between quantitative characteristics that can be measured on a metric scale (such as body weight or income) and qualitative characteristics (such as gender or color). In the second case, one also speaks of a categorical characteristic , since characteristics are given in the form of a category .
Statistical variable vs. Random variable
They are two sides of a variable and they define the same characteristics. Behind a statistical variable, however, there is a population or a sample and the relative and absolute frequencies associated with the characteristics. Behind a random variable is a random experiment (model) and, associated with the characteristic values, probabilities.
Example (choice):
- Random variable
- There is a predetermined probability that a party will be elected. The random variable : party elected has two possible characteristics: party elected or party not elected . The probability that the party will be elected and the probability that the party will not be elected is .
- Statistical variable
- There are from voters who voted for the party. The statistical variable : party elected has two possible values: party elected or party not elected . The relative frequency with which the party is elected, and that at which the party was not elected .
literature
- Rainer Schlittgen : Introduction to Statistics. 9th edition. Oldenbourg Wissenschaftsverlag, Oldenbourg 2000, ISBN 3-486-27446-5
- Peter Bohley: Statistics - Introductory textbook for economists and social scientists. 6th edition. Oldenbourg Wissenschaftsverlag, Oldenbourg 1996, ISBN 3-486-23497-8