Statistics

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Statistics
Including: Single Var, Fit Data and Summary Statistics.

The menu Statistics
Keyboard access:  [STAT]

 



Single-Var                                                           
Keyboard access:
 [STAT][Single-Var]

Example:
To DAT: [[1 5][3 3] [ 7 2] [9 6] [3 8] [2 6]]

TYPE: Sample
MEAN:4.1666666667...
STD DEV:3.125666...
VARIANCE:9.766666...
TOTAL: 25
MAXIMUM: 9
MINIMUM: 1

TYPE: Population
MEAN:4.1666666667...
STD DEV:2.8528737...
VARIANCE:8.138888...
TOTAL: 25
MAXIMUM: 9
MINIMUM: 1

Summary Stats                                                        
Keyboard access:
 [STAT][Summary stats]

Example:
To DAT: [[1 5][3 3] [ 7 2] [9 6] [3 8] [2 6]]

X:25

Y:30

X2:153

Y2:134:

XY:118
N:6

Fit Data                                                             

Keyboard access:
 [STAT][Fit data]

Example:
To DAT: [[1 5][3 3] [ 7 2] [9 6] [3 8] [2 6]]

Logarithm Fit
'5.664034+-56646111*LN(X)'
correlation:-.208890217097
covariance:-.36974928012

Exponential Fit
'5.40143100114*EXP(-4.223223061E-2)'
correlation:-.255960001612
covariance:-.412468119051

Linear Fit
'5.59726962457+-.143344709898*X'
correlation:-.204472183243
covariance:-1.4

Power Fit
'5.63213404451*X^-.185792485677'
correlation:-.291106339392
covariance:-.12127335139

Best Fit
'5.63213404451*X^-.185792485677'
correlation:-.291106339392
covariance:-.12127335139

Best Fit is the Fit with covariance, in absolute value, closest to 1.

PRED

You can know the value of X for a given value of Y
or vice-versa using PRED into FIT DATA function.
Choose the FIT type and press PRED in menu, fill out the fields for
X or Y and press PRED and HP48 give you the result.

To DAT: [[1 5][3 3] [ 7 2] [9 6] [3 8] [2 6]]
we have:
X: 25.0952380951 Y:2
X: 5.5 Y:4.80887372013

Where the red numbers are the ones we give to HP48 predict the value
and the green numbers, the result.
Press EDIT, in menu to see the number in full standard format.