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unstrict inequality signs (less-than or equals to sign and greater-than or equals to sign) 1670 (with the horizontal bar over the inequality sign, rather than below it) John Wallis: 1734 (with double horizontal bar below the inequality sign) Pierre Bouguer
A mathematical symbol is a figure or a combination of figures that is used to represent a mathematical object, an action on mathematical objects, a relation between mathematical objects, or for structuring the other symbols that occur in a formula. As formulas are entirely constituted with symbols of various types, many symbols are needed for ...
The less-than sign with the equals sign, <=, may be used for an approximation of the less-than-or-equal-to sign, ≤. ASCII does not have a less-than-or-equal-to sign, but Unicode defines it at code point U+2264. In BASIC, Lisp-family languages, and C-family languages (including Java and C++), operator <= means "less than or equal to".
The figure illustrates the percentile rank computation and shows how the 0.5 × F term in the formula ensures that the percentile rank reflects a percentage of scores less than the specified score. For example, for the 10 scores shown in the figure, 60% of them are below a score of 4 (five less than 4 and half of the two equal to 4) and 95% are ...
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.
fullwidth plus sign u+ff1c ＜ fullwidth less-than sign u+ff1d ＝ fullwidth equals sign u+ff1e ＞ fullwidth greater-than sign u+ff3c \ fullwidth reverse solidus u+ff3e ^ fullwidth circumflex accent u+ff5c ｜ fullwidth vertical line u+ff5e ～ fullwidth tilde u+ffe2 ￢ fullwidth not sign u+ffe9 ￩ halfwidth leftwards arrow u+ffea ...
Cumulative distribution function for the exponential distribution Cumulative distribution function for the normal distribution. In probability theory and statistics, the cumulative distribution function (CDF) of a real-valued random variable, or just distribution function of , evaluated at , is the probability that will take a value less than or equal to .