I selecting the regression type, I displaying regression calculation results – Casio FX-9750GII User Manual

Page 150

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Example Input the two sets of data shown below and plot the data on a scatter

diagram. Next, perform logarithmic regression on the data to display the
regression parameters, and then draw the corresponding regression
graph.

0.5, 1.2, 2.4, 4.0, 5.2 (

x

List)

–2.1, 0.3, 1.5, 2.0, 2.4 (

y

List)

 K STAT

 ? DU@ AUA CUCUD AUC

A @U? BU@ DUAUA CU

(GRPH)(SET)A(Scat))(GPH1)

 (CALC)(E)(Log)

 (DRAW)

• You can perform trace on a regression graph. You cannot perform trace scroll.

• Input a positive integer for frequency data. Other types of values (decimals, etc.) cause an

error.

I Selecting the Regression Type

After you graph paired-variable statistical data, you can use the function menu at the bottom of
the display to select from a variety of different types of regression.

• {

ax

+

b

}/{

a

+

bx

}/{Med}/{X^2}/{X^3}/{X^4}/{Log}/{

ae

^

bx

}/{

ab

^

x

}/{Pwr}/{Sin}/{Lgst} ...

{linear regression (

ax

+

b

form)}/{linear regression (

a

+

bx

form)}/{Med-Med}/{quadratic

regression}/{cubic regression}/{quartic regression}/{logarithmic regression}/{exponential
regression (

ae

bx

form)}/{exponential regression (

ab

x

form)}/{power regression}/

{sinusoidal regression}/{logistic regression} calculation and graphing

• {2VAR}... {paired-variable statistical results}

I Displaying Regression Calculation Results

Whenever you perform a regression calculation, the regression formula parameter (such as

a

and

b

in the linear regression

y

=

ax

+

b

) calculation results appear on the display. You can use

these to obtain statistical calculation results.

Regression parameters are calculated as soon as you press a function key to select a
regression type, while a graph is on the display.

The following parameters are used by linear regression, logarithmic regression, exponential
regression, and power regression.

r

.............. correlation coefficient

r

2

............. coefficient of determination

MSe

......... mean square error

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