Chapter 2: Main Application 86
u normCDf [Action][Distribution/Inv.Dist][Continuous][normCDf]
Function: Returns the cumulative probability of a normal distribution between a lower bound and an upper
bound.
Syntax: normCDf(lower value, upper value[,
σ
,
μ
)]
• When
σ
and
μ
are skipped,
σ
= 1 and
μ
= 0 are used.
Calculation Result Output:
prob , z Low, z Up
Example: To determine the normal probability density when lower bound
value = −
∞, upper bound value = 36,
σ
= 2,
μ
= 35
u invNormCDf [Action][Distribution/Inv.Dist][Inverse][invNormCDf]
Function: Returns the boundary value(s) of a normal cumulative distribution probability for specified values.
Syntax: invNormCDf([tail setting, ]area value[,
σ
,
μ
)]
• When
σ
and
μ
are skipped,
σ
= 1 and
μ
= 0 are used.
• “tail setting” displays the probability value tail specification, and Left, Right, or Center can be specified. Enter
the following values or letters to specify:
Left: −1, “L”, or “l”
Center: 0, “C”, or “c”
Right: 1, “R”, or “r”
When input is skipped, “Left” is used.
• When one argument is omitted (resulting in three arguments), Tail=Left.
• When two arguments are omitted (resulting in two arguments), Tail=Left,
μ
=0.
• When three arguments are omitted (resulting in one argument), Tail=Left,
σ
=1,
μ
=0.
• When “tail setting” is Center, the lower bound value is returned.
Calculation Result Output:
x
1
InvN, x
2
InvN
Example: To determine the upper bound value when tail setting = Left, area
value = 0.7,
σ
= 2,
μ
= 35
u tPDf [Action][Distribution/Inv.Dist][Continuous][tPDf]
Function: Returns the Student’s t probability density for a specified value.
Syntax: tPDf(x, df [ ) ]
Calculation Result Output:
prob
Example: To determine the Student’s t probability density when x = 2, df = 5
u tCDf [Action][Distribution/Inv.Dist][Continuous][tCDf]
Function: Returns the cumulative probability of a Student’s t distribution between a lower bound and an upper
bound.
Syntax: tCDf(lower value, upper value,
df [ ) ]
Calculation Result Output:
prob, tLow, tUp
Example: To determine the Student’s
t distribution probability when
lower value = 1.5, upper value = ∞, df = 18
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