Gu
23
D The table below indicates the key operations to be used to call in the
results in the case of quadratic regression.
Recall the value: Execute this key operation:
c
e
d
Regression coefficient C
q
r
t
D The values in the table above can be used inside expressions in the
same way as variables.
Linear regression
The regression equation for linear regression is: y = A+Bx.
Example 1:
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
In REG mode: (Lin)
(SCI) (Stat clear)
10
1003
Note!
Each time you press the
key to register the data entered, the
number of data entries made up to that time appears in the display
(n-value).
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
2
) and
sample covariance.
REG
n=
1.
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