LEXIBOOK SC460 Owner's Manual page 71

For quadratic regression
^
[SHIFT] [S-VAR]
X1
[ ][ ][ ] 1
^
[SHIFT] [S-VAR]
X2
[ ][ ][ ] 2
^
[SHIFT] [S-VAR]
Y
[ ][ ][ ] 3
[SHIFT] [S-VAR]
C
[ ][ ] 3
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
Y 5
We switch to the two-variable statistics mode and linear regression:
[MODE] 3
1
[SHIFT][CLR] 1 [=] -> clear
We begin the data input:
2 [,] 5 [DT] [DT]
...
21 [,] 40 [SHIFT] [;] 3 [DT] -> n= I
We check n:
[SHIFT] [S-SUM] 3 [=] -> n= |
We display the results of the linear regression:
[SHIFT] [S-VAR] [ ][ ] 1 [=]
[SHIFT] [S-VAR] [ ][ ] 2 [=]
[SHIFT] [S-VAR] [ ][ ] 3 [=]
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 [=]
We estimate the value of x as from y=46:
46 [SHIFT] [S-VAR] [ ][ ][ ] 1 [=] -> 46x
The statistical keys of your calculator allow you to easily display all the
intermediate results, for example:
[SHIFT] [S-SUM] [ ] 3 [=] -> 3,203.
[SHIFT] [S-VAR] [ ] 2 [=] -> 14.50967306
Copyright © Lexibook 007
SC460IM0237.indb 71
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.
2 12
5 24
-> REG is displayed
->
-> n= I 2.
17.
7.
-> A | 1.050261097
-> B | 1.826044386
-> r | 0.9951763432
-> 3
15 21 21
25 40 40
y ^
| 6.528394256
^
| 24.61590706
∑xy
y n
21
40
71
20/6/07 15:28:12