•The values in the above tables can be used inside of expressions the same way you use variables.
uLinear 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.Fi- nally, calculate the coefficient of determination (r2) and sample
covariance 
.
In the REG Mode:
1(Lin)
AB1(Scl) =(Stat clear)
10 P1003 S | n= | REG | ||
1. | ||||
|
|
| ||
| Each time you press Sto register your input, | |||
| the number of data input up to that point is | |||
| indicated on the display (n value). | |||
| 15 | P1005 S | ||
| 20 P1010 S25 | P1011 S | ||
| 30 | P1014 S | ||
Regression Coefficient A = 997.4 | A Xr r 1 = | |||
Regression Coefficient B = 0.56 | A Xr r 2 = | |||
Correlation Coefficient r = 0.982607368
A Xr r 3 =
Atmospheric Pressure at 18°C = 1007.48
18 A Xr r r 2 =
30