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Copyright © Lexibook 007
ENGLISH
X1
X2
Y
C
Displays the first value of x estimated by
regression for the value of y entered.
Displays the second value of x estimated by
regression for the value of y entered.
Displays the value of y estimated by
regression for the value of x entered.
Calculates the value of the coefficient C.
[SHIFT] [S-VAR]
[ ][ ][ ] 1
[SHIFT] [S-VAR]
[ ][ ][ ] 2
[SHIFT] [S-VAR]
[ ][ ][ ] 3
[SHIFT] [S-VAR]
[ ][ ] 3
For quadratic regression
Practical examples:
Linear Regression:
In the following table, x is the length in mm and y the weight in mg of a
caterpillar/butterfly during the different stages of its development.
X
2
2
12
15
21
21
21
Y
5
5
24
25
40
40
40
We switch to the two-variable statistics mode and linear regression:
[MODE] 3
->
REG
is displayed
1
->
[SHIFT][CLR] 1 [=] -> clear
We begin the data input:
2 [,] 5 [DT] [DT]
-> n= I 2.
…
21 [,] 40 [SHIFT] [;] 3 [DT] -> n= I 17.
We check n:
[SHIFT] [S-SUM] 3 [=] -> n= | 7.
We display the results of the linear regression:
[SHIFT] [S-VAR] [ ][ ] 1 [=]
-> A | 1.050261097
[SHIFT] [S-VAR] [ ][ ] 2 [=]
-> B | 1.826044386
[SHIFT] [S-VAR] [ ][ ] 3 [=]
-> r | 0.9951763432
r is greater than √3/2 = 0.866 approximately, the validity of the regression is
verified.
Due to the linear regression, we estimate the value of y as from x=3 :
3 [SHIFT] [S-VAR] [ ][ ][ ] 2 [=]
-> 3
| 6.528394256
We estimate the value of x as from y=46:
46 [SHIFT] [S-VAR] [ ][ ][ ] 1 [=] -> 46x | 24.61590706
The statistical keys of your calculator allow you to easily display all the
intermediate results, for example:
[SHIFT] [S-SUM] [ ] 3 [=] -> 3,203.
∑xy
[SHIFT] [S-VAR] [ ] 2 [=] -> 14.50967306
y n
y^
^
^
^
^
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