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The English language has a number of words that denote specific or approximate quantities that are themselves not numbers. [1] Along with numerals, and special-purpose words like some, any, much, more, every, and all, they are Quantifiers. Quantifiers are a kind of determiner and occur in many constructions with other determiners, like articles ...
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.
The probability of an event is a number between 0 and 1; the larger the probability, the more likely an event is to occur. [note 1] [1] [2] This number is often expressed as a percentage (%), ranging from 0% to 100%. A simple example is the tossing of a fair (unbiased) coin.
Many words of different parts of speech indicate number or quantity. Such words are called quantifiers. Examples are words such as every, most, least, some, etc. Numerals are distinguished from other quantifiers by the fact that they designate a specific number. [3] Examples are words such as five, ten, fifty, one hundred, etc.
Odds can also be expressed as a number, by dividing the terms in the ratio—in this case it is unique (different fractions can represent the same rational number). Odds as a ratio, odds as a number, and probability (also a number) are related by simple formulas, and similarly odds in favor and odds against, and probability of success and ...
Also unlike common nouns, English pronouns show distinctions in case (e.g., I, me, mine), person (e.g., I, you) and gender (e.g., he, she). Though both common nouns and pronouns show number distinction in English, they do so differently: common nouns tend to take an inflectional ending (–s) to mark
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If the number of trials were increased to 10,000, the probability of it happening at least once in 10,000 trials rises to ( 1 − 0.999 10000 ≈ 0.99995, or ) 99.995%. In other words, a highly unlikely event, given enough independent trials with some fixed number of draws per trial, is even more likely to occur.