Casio fx-CP400 - Page 87

Chapter 2: Main Application 87
Important!
See “Important!” under “invBinomialCDf” on page 86.
Example: To determine the minimum number of trials when
prob = 0.8074,
 = 2.26
u geoPDf [Action][Distribution/Inv.Dist][Discrete][geoPDf]
Function: Returns the probability in a geometric distribution that the success will occur on a specified trial.
Syntax: geoPDf( x , pos [ ) ]
Calculation Result Output:
prob
Example: To determine the geometric probability when x = 6, pos = 0.4
u geoCDf [Action][Distribution/Inv.Dist][Discrete][geoCDf]
Function: Returns the cumulative probability in a geometric distribution that the success will occur between
specified lower value and upper value.
Syntax: geoCDf(lower value, upper value, pos [ ) ]
Calculation Result Output:
prob
Example: To determine the geometric probability when lower value = 2,
upper value = 3, pos = 0.5
u invGeoCDf [Action][Distribution/Inv.Dist][Inverse][invGeoCDf]
Function: Returns the minimum number of trials of a geometric cumulative probability distribution for specified
values.
Syntax: invGeoCDf(
prob , pos [ ) ]
Calculation Result Output:
x Inv, ½ x Inv
Important!
See “Important!” under “invBinomialCDf” on page 86.
Example: To determine the minimum number of trials when
prob = 0.875,
pos = 0.5
u hypergeoPDf [Action][Distribution/Inv.Dist][Discrete][hypergeoPDf]
Function: Returns the probability in a hypergeometric distribution that the success will occur on a specified
trial.
Syntax: hypergeoPDf(
x , n , M , N [ ) ]
Calculation Result Output:
prob
Example: Determine the hypergeometric probability when x = 1, n = 5,
M = 10, N = 20.
u hypergeoCDf [Action][Distribution/Inv.Dist][Discrete][hypergeoCDf]
Function: Returns the cumulative probability in a hypergeometric distribution that the success will occur
between specified lower value and upper value.
Syntax: hypergeoCDf(lower value, upper value,
n , M , N [ ) ]
Calculation Result Output:
prob
Example: Determine the hypergeometric cumulative distribution when lower
value = 0, upper value = 1, n = 5, M = 10, N = 20.