Casio FX-9750GII User Manual

Page 190

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6-50

• Inverse Hypergeometric Cumulative Distribution

(DIST)(

E

)

(H.GEO)(InvH)

Inverse Hypergeometric Cumulative Distribution calculates
the minimum number of trials of a hypergeometric
cumulative probability distribution for specified values.

Calculation Result Output Examples

When a list is specified

When variable (

x

) is specified

• There is no graphing for Inverse Hypergeometric Cumulative Distribution.

Important!

When executing the Inverse Hypergeometric Cumulative Distribution calculation, the calculator
uses the specified Area value and the value that is one less than the Area value minimum
number of significant digits (

>Area value) to calculate minimum number of trials values.

The results are assigned to system variables

x

Inv (calculation result using Area) and

>

x

Inv

(calculation result using

>Area). The calculator always displays the

x

Inv value only. However,

when the

x

Inv and

>

x

Inv values are different, the message will appear with both values.

The calculation results of Inverse Hypergeometric Cumulative Distribution are integers.
Accuracy may be reduced when the first argument has 10 or more digits. Note that even
a slight difference in calculation accuracy affects calculation results. If a warning message
appears, check the displayed values.

8. Input and Output Terms of Tests, Confidence

Interval, and Distribution

(All models except fx-7400G

II

)

The following explains the input and output terms that are used by tests, confidence interval,
and distribution.

I Input Terms

Data ...................................data type

ƫ

(1-Sample

Z

Test) ...........population mean value test conditions (“

x

ƫ

0

” specifies two-tail test,

“<

ƫ

0

” specifies lower one-tail test, “>

ƫ

0

” specifies upper one-tail

test.)

ƫ

1

(2-Sample

Z

Test) ..........population mean value test conditions (“

x

ƫ

2

” specifies two-tail test,

“<

ƫ

2

” specifies one-tail test where sample 1 is smaller than sample

2, “>

ƫ

2

” specifies one-tail test where sample 1 is greater than

sample 2.)

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