Casio fx-3650P, fx-3950P u Linear Regression, yσn, Σx2y, Σx3, Σx4, A Xr, A Xr, 10°C, 15°C, 20°C, 25°C, 30°C, A Xr r, A Xr r, A Xr r, A Ur r, A Ur r, A Ur r, A Xr r, A Xr r r, A Xr r r

To recall this type of value: Perform this key operation:

yσn	A Xr 2
yσn-1	A Xr 3
Regression coefficient A	A Xr r 1
Regression coefficient B	A Xr r 2

Regression calculation other than quadratic regression

Correlation coefficient r	A Xr r 3
m	A Xr r r 1

nA Xr r r 2

•The following table shows the key operations you should use to recall results in the case of quadratic regression.

To recall this type of value: Perform this key operation:

Σx3	A Ur r 1
Σx2y	A Ur r 2
Σx4	A Ur r 3
Regression coefficient C	A Xr r 3
m1	A Xr r r 1
m2	A Xr r r 2
n	A Xr r r 3

•The values in the above tables can be used inside of expressions the same way you use variables.

u Linear Regression

•The regression formula for linear regression is: y = A + Bx.•Example: Atmospheric Pressure vs. Temperature

Temperature	Atmospheric
	Pressure
10°C	1003 hPa
15°C	1005 hPa
20°C	1010 hPa
25°C	1011 hPa
30°C	1014 hPa

Perform linear regression to determine the regression formula terms and correlation coefficient for the data nearby. Next, use the regression formula to estimate atmospheric pressure at 18°C and temperature at 1000 hPa. Finally, calculate the coefficient of determination (r2) and

sample covariance .

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