writer
6,694
edits
Changes
Jump to navigation
Jump to search
Manuals/calci/DISCRETEDISTRIBUTED (view source)
Revision as of 19:14, 20 September 2017
, 19:14, 20 September 2017Created page with "<div style="font-size:30px">'''DISCRETEDISTRIBUTED (Numbers,Values,Probability) '''</div><br/> *<math>Thing</math> is any value to test. ==Description== *This function shows ..."
<div style="font-size:30px">'''DISCRETEDISTRIBUTED (Numbers,Values,Probability) '''</div><br/>
*<math>Thing</math> is any value to test.
==Description==
*This function shows the value of Discrete distribution.
*The Discrete Uniform distribution is a symmetric probability distribution whereby a finite number of values are equally likely to be distributed.
*So every one of n values has equal probability 1/n.
*Unlike a continuous distribution which has an infinite number of outcomes,a discrete distribution is characterized by a limited number of possible observations.
*Discrete distribution is frequently used in statistical modeling and computer programming.
*The discrete uniform distribution itself is inherently non-parametric.
*Consider an interval <math>[a,b]</math>, with these conventions, the cumulative distribution function (CDF) of the discrete uniform distribution can be expressed, for any <math>k ∈ [a,b], as F(k;a,b)=k-a+1/b-a+1.
*This function will return the result as error when
1.Any one of the parameter is non numeric.
2.The value of a and b is<0.
*<math>Thing</math> is any value to test.
==Description==
*This function shows the value of Discrete distribution.
*The Discrete Uniform distribution is a symmetric probability distribution whereby a finite number of values are equally likely to be distributed.
*So every one of n values has equal probability 1/n.
*Unlike a continuous distribution which has an infinite number of outcomes,a discrete distribution is characterized by a limited number of possible observations.
*Discrete distribution is frequently used in statistical modeling and computer programming.
*The discrete uniform distribution itself is inherently non-parametric.
*Consider an interval <math>[a,b]</math>, with these conventions, the cumulative distribution function (CDF) of the discrete uniform distribution can be expressed, for any <math>k ∈ [a,b], as F(k;a,b)=k-a+1/b-a+1.
*This function will return the result as error when
1.Any one of the parameter is non numeric.
2.The value of a and b is<0.