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The ratio type takes its name from the fact that measurement is the estimation of the ratio between a magnitude of a continuous quantity and a unit of measurement of the same kind (Michell, 1997, 1999). Most measurement in the physical sciences and engineering is done on ratio scales.
The concept of data type is similar to the concept of level of measurement, but more specific. For example, count data requires a different distribution (e.g. a Poisson distribution or binomial distribution) than non-negative real-valued data require, but both fall under the same level of measurement (a ratio scale).
A useful summary of such data is the population pyramid. It provides data about the sex and age distribution of the population in an accessible graphical format. [3] Another summary is called the life table. For a cohort of persons born in the same year, it traces and projects their life experiences from birth to death.
A percentage change is a way to express a change in a variable. It represents the relative change between the old value and the new one. [6]For example, if a house is worth $100,000 today and the year after its value goes up to $110,000, the percentage change of its value can be expressed as = = %.
The dependency ratio is an age-population ratio of those typically not in the labor force (the dependent part ages 0 to 14 and 65+) and those typically in the labor force (the productive part ages 15 to 64). It is used to measure the pressure on the productive population.
Data may be collected, presented and summarised, in one of two methods called descriptive statistics. Two elementary summaries of data, singularly called a statistic, are the mean and dispersion. Whereas inferential statistics interprets data from a population sample to induce statements and predictions about a population. [6] [7] [5]
When comparing data from a specific country or region, using a standard population from that country or region means that the age-adjusted rates are similar to the true population rates. [6] On the other hand, standardizing data using a widely used standard such as the WHO standard population allows for easier comparison with published statistics.
Age stratification; Aggregate data; ... Exact statistics; Exact test; Examples of Markov chains; ... Structured data analysis (statistics)