Casio E-10 Guide de l'utilisateur télécharger pdf (Page 24)

E-23

(SETUP)A(STAT)(ON)

(STAT)(1-VAR)

1  2  3  4  5 AC

1 2  3  2 

(STAT)(Var)(M)

(STAT)(Var)(S

x)

Results: Mean: 3 Population Standard Deviation: 1.154700538

To calculate the linear regression and logarithmic regression

correlation coefficients for the following paired-variable data and

determine the regression formula for the strongest correlation: (

x, y)

= (20, 3150), (110, 7310), (200, 8800), (290, 9310). Specify Fix 3

(three decimal places) for results.

(SETUP)A(STAT)(OFF)

(SETUP)(Fix)

(STAT)(A+BX)

20  110  200  290 AC

3150  7310 8800 9310

(STAT)(Reg)(r)

(STAT)(Type)(In X)

(STAT)(Reg)(r)

(STAT)(Reg)(A)

(STAT)(Reg)(B)

Results: Linear Regression Correlation Coefficient: 0.923

Logarithmic Regression Correlation Coefficient: 0.998

Logarithmic Regression Formula:

y = –3857.984 + 2357.532lnx

Calculating Estimated Values

Based on the regression formula obtained by paired-variable statistical

calculation, the estimated value of

y can be calculated for a given x-value.

The corresponding

x-value (two values, x

and x

, in the case of quadratic

regression) also can be calculated for a value of

y in the regression

formula.

To determine the estimate value for y when x = 160 in the

regression formula produced by logarithmic regression of the data

. Specify Fix 3 for the result. (Perform the following operation

after completing the operations in

 160 (STAT)(Reg)(L)

Result: 8106.898

Important: Regression coefficient, correlation coefficient, and estimated

value calculations can take considerable time when there are a large number

of data items.



STAT

FIX

STAT

FIX

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