11–8 Statistical
Operations
File name 32sii-Manual-E-0424
Printed Date : 2003/4/24 Size : 17.7 x 25.2 cm
L.R. (Linear Regression) Menu
Menu Label
Description
{
º
ˆ
}
Estimates (predicts)
x
for a given hypothetical value of
y
, based on the line calculated to fit the data.
{
¸
ˆ
}
Estimates (predicts)
y
for a given hypothetical value of
x
, based on the line calculated to fit the data.
{
T
}
Correlation coefficient for the (
x
,
y
) data. The
correlation coefficient is a. number in the range –1
t1 that measures how closely the calculated
line fits the data.
{
P
}
Slope of the calculated line.
{
E
}
y
–intercept of the calculated line.
To find an estimated value for
x
(or
y
), key in a given hypothetical value
for
y
(or
x
), then press
{
,
{
º
ˆ
} (or
{
,
{
¸
ˆ
}).
To find the values that define the line that best fits your data, press
{
,
followed by {
T
}, {
P
}, or {
E
}.
Example:
Curve Fitting.
The yield of a new variety of rice depends on its rate of fertilization with
nitrogen. For the following data, determine the linear relationship: the
correlation coefficient, the slope, and the
y
–intercept.
X, Nitrogen Applied
(kg per hectare)
0.00
20.00 40.00 60.00 80.00
Y, Grain Yield
(metric tons per hectare)
4.63
5.78
6.61
7.21
7.78
Keys: Display:
Description:
z
b
{
´
}
Clears all, previous statistical
