
•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 | Perform linear regression to de- | |||||
| Pressure | termine the regression formula | ||||||
| 
 | |||||||
| 10°C | 1003 hPa | ||||||
| terms and correlation coefficient | |||||||
| 15°C | 1005 hPa | ||||||
| for the data nearby. Next, use | |||||||
| 20°C | 1010 hPa | ||||||
| the regression formula to esti- | |||||||
| 25°C | 1011 hPa | ||||||
| mate atmospheric pressure at | |||||||
| 30°C | 1014 hPa | ||||||
| 18°C and temperature at 1000 | |||||||
| 
 | 
 | ||||||
| 
 | 
 | hPa. Finally, calculate the coeffi- | |||||
| 
 | 
 | cient of determination (r2) and | |||||
| 
 | 
 | sample covariance | |||||
| 
 | 
 | 
 | 
 | 
 | 
 | . | |
| 
 | 
 | 
 | |||||
| In the REG Mode: | 
 | |
| 1(Lin) | 
 | |
| AB1(Scl) =(Stat clear) | REG | |
| 10 P1003 S n= | ||
| 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 P 1005 S
20 P1010 S 25 P1011 S
30 P1014 S
| Regression Coefficient A = 997.4 | A Xrr 1= | 
| Regression Coefficient B = 0.56 | A Xrr 2= | 
| Correlation Coefficient r = 0.982607368 | A Xrr 3= | 
| Atmospheric Pressure at 18°C = 1007.48 | 
 | 
18 AXr rr 2=
Temperature at 1000 hPa = 4.642857143