Linear Regression - Olympia LCD 9210 Benutzerhandbuch

The table below indicates the key operations to be used to call in the
D
results in the case of quadratic regression.
Recall the value:
Regression coefficient C
The values in the table above can be used inside expressions in the
D
same way as variables.

Linear regression

The regression equation for linear regression is: y = A+Bx.
Example 1: Atmospheric pressure vs. temperature
Temperature
10°C
15°C
20°C
25°C
30°C
In REG mode:
Note!
Each time you press the
number of data entries made up to that time appears in the display
(n-value).
tanx
−1
cos x
∑
χ
4
1
x
χ
y
y
Atmospheric
pressure
1003 hPa
1005 hPa
1010 hPa
1011 hPa
1014 hPa
(Lin)
Execute this key operation:
Execute linear regression in order to determine the terms and
correlation coefficient of the regression equation for the
adjacent data. Then use the regression equation to estimate
the atmospheric pressure at –5°C and the temperature at 1000
hPa. Finally, calculate the coefficient of determination (r
sample covariance.
(SCI) (Stat clear)
10 1003
key to register the data entered, the
59
2
) and
REG
n=
1.