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Random variables are usually written in upper case Roman letters, such as or and so on. Random variables, in this context, usually refer to something in words, such as "the height of a subject" for a continuous variable, or "the number of cars in the school car park" for a discrete variable, or "the colour of the next bicycle" for a categorical variable.
¯ = sample mean of differences d 0 {\displaystyle d_{0}} = hypothesized population mean difference s d {\displaystyle s_{d}} = standard deviation of differences
Historically, upper-case letters were used for representing points in geometry, and lower-case letters were used for variables and constants. Letters are used for representing many other types of mathematical object. As the number of these types has increased, the Greek alphabet and some Hebrew letters have also come to be used.
Cohen's kappa measures the agreement between two raters who each classify N items into C mutually exclusive categories. The definition of is =, where p o is the relative observed agreement among raters, and p e is the hypothetical probability of chance agreement, using the observed data to calculate the probabilities of each observer randomly selecting each category.
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the population mean or expected value in probability and statistics; a measure in measure theory; micro-, an SI prefix denoting 10 −6 (one millionth) Micrometre or micron (retired in 1967 as a standalone symbol, replaced by "μm" using the standard SI meaning) the coefficient of friction in physics; the service rate in queueing theory
It is used in the International System of Units, where it has the symbol k, in lowercase. The prefix kilo is derived from the Greek word χίλιοι ( chilioi ), meaning "thousand". In 19th century English it was sometimes spelled chilio, in line with a puristic opinion by Thomas Young .
In statistics, the conditional probability table (CPT) is defined for a set of discrete and mutually dependent random variables to display conditional probabilities of a single variable with respect to the others (i.e., the probability of each possible value of one variable if we know the values taken on by the other variables).