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min(x)* ...... minimum value
Q
1
* ...... first quartile
Med* ...... median
Q
3
* ...... third quartile
max(x)* ...... maximum value
– [Statistics] > [Min/Max] (Paired-Variable Data Only)
min(x), min(y) ...... minimum value
max(x), max(y) ...... maximum value
– [Statistics] > [Regression] (Paired-Variable Data Only)
For quadratic regression
a, b, c ...... regression coefficients for quadratic regression
x
ˆ
1
, xˆ
2
...... Functions for determining x
1
and x
2
estimated values for an
input y-value. For the argument, input the value of y immediately before
the x
ˆ
1
or x
ˆ
2
function.
y
ˆ ...... Function for determining the y estimated value for an input x-
value. For the argument, input the value of x immediately before this
function.
For non-quadratic regression
a, b ...... regression coefficients
r ...... correlation coefficient
x
ˆ ...... Function for determining x estimated value for an input y-value.
For the argument, input the value of y immediately before this function.
y
ˆ ...... Function for determining the y estimated value for an input x-
value. For the argument, input the value of x immediately before this
function.
For an example of the operation to determine estimated values, see
"Calculating Estimated Values (Paired-Variable Data Only)" (page
70).
Calculating Estimated Values (Paired-Variable Data Only)
Based on the regression equation obtained by paired-variable statistical
calculation, the estimated value of y can be calculated for a given x-value.
The corresponding x-value (two values, x
1
and x
2
, in the case of quadratic
regression) also can be calculated for a value of y in the regression
equation.
Example 8: To determine the estimated value for y when x = 5.5 in the
regression equation produced by linear regression of the data input in
Example 4 (page 63)
70
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