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This is a list of statistical procedures which can be used for the analysis of categorical data, also known as data on the nominal scale and as categorical variables. General tests [ edit ]
In statistics and research design, an index is a composite statistic – a measure of changes in a representative group of individual data points, or in other words, a compound measure that aggregates multiple indicators. [1] [2] Indices – also known as indexes and composite indicators – summarize and rank specific observations. [2]
A variable category that is often measured in survey research are demographic variables, which are used to depict the characteristics of the people surveyed in the sample. [3] Demographic variables include such measures as ethnicity, socioeconomic status, race, and age. [3]
Demographic statistics are measures of the characteristics of, or changes to, a population. Records of births, deaths, marriages, immigration and emigration and a regular census of population provide information that is key to making sound decisions about national policy.
When multiple items measure the same variable in a reliable and valid way, they are collectively referred to as a multi-item scale, or a psychometric scale. The following types of reliability and validity should be established for a multi-item scale: internal reliability , test-retest reliability (if the variable is expected to be stable over ...
Because variables conforming only to nominal or ordinal measurements cannot be reasonably measured numerically, sometimes they are grouped together as categorical variables, whereas ratio and interval measurements are grouped together as quantitative variables, which can be either discrete or continuous, due to their numerical nature.
A "parameter" is to a population as a "statistic" is to a sample; that is to say, a parameter describes the true value calculated from the full population (such as the population mean), whereas a statistic is an estimated measurement of the parameter based on a sample (such as the sample mean).
Some measures that are commonly used to describe a data set are measures of central tendency and measures of variability or dispersion. Measures of central tendency include the mean , median and mode , while measures of variability include the standard deviation (or variance ), the minimum and maximum values of the variables, kurtosis and ...