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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.
The Demography of the World Population from 1950 to 2100. Data source: United Nations — World Population Prospects 2017. Demography (from Ancient Greek δῆμος (dêmos) ' people, society ' and -γραφία (-graphía) ' writing, drawing, description ') [1] is the statistical study of human populations: their size, composition (e.g., ethnic group, age), and how they change through the ...
The values are ordered in a logical way and must be defined for each variable. Domains can be bigger or smaller. The smallest possible domains have those variables that can only have two values, also called binary (or dichotomous) variables. Bigger domains have non-dichotomous variables and the ones with a higher level of measurement.
A spurious relationship is a relationship in which the relation between two variables can be explained by a third variable. Moreover, in survey research, correlation coefficients between two variables might be affected by measurement error, what can lead to wrongly
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.
In survey research, the design effect is a number that shows how well a sample of people may represent a larger group of people for a specific measure of interest (such as the mean). This is important when the sample comes from a sampling method that is different than just picking people using a simple random sample .