Continuous univariate statistical distributions are functions that describe the likelihood that a random variable, say, X, falls within a given range. Let P (a Xb) represent the probability that X falls within the range [a, b].

A numerically valued variable is said to be continuous if, in any unit of measurement, whenever it can take on the values a and b. If the random variable X can assume an infinite and uncountable set of values, it is said to be a continuous random variable.

If X can take any specific value on the real line, the probability of any specific value is effectively zero (because we'd have a=b, which means no range). As a result, continuous probability distributions are frequently described in terms of their cumulative distribution function, F(x).

To learn more about univariated data

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7 0

1 year ago

its back to school time and fred wants to buy sneakers. the sneakers cost $57 and he has 52.80$ in the bank. he also has seven q

Andrew [12]

$1.78 is your answer

5 0

3 years ago

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