Results:
Results:
Mean: 3, Population Standard Deviation: 1,154700538
Example 3:
To calculate the linear regression and logarithmic regression
correlation coefficients for the following paired-variable data and determine
the regression formula for the strongest correlation: (
x
;
y
) = (20; 3150),
(110; 7310), (200; 8800), (290; 9310). Specify Fix 3 (three decimal places)
for results.
(SETUP)
(STAT)
(OFF)
(SETUP)
(Fix)
(STAT)
(A+BX)
20
110
200
290
3150
7310
8800
9310
(STAT/DIST)
(Reg)
(
r
)
0,923
(STAT/DIST)
(Type)
(ln X)
(STAT/DIST)
(Reg)
(
r
)
0,998
(STAT/DIST)
(Reg)
(A)
-3857,984
(STAT/DIST)
(Reg)
(B)
2357,532
Linear Regression Correlation Coefficient: 0,923
Logarithmic Regression Correlation Coefficient: 0,998
Logarithmic Regression Formula:
y
= -3857,984 + 2357,532ln
x
Calculating Estimated Values
Based on the regression formula 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
formula.
Example 4:
To determine the estimate value for
x
when
y
= -130 in the
regression formula produced by logarithmic regression of the data in
Example 3. Specify Fix 3 for the result. (Perform the following operation
after completing the operations in Example 3.)
130
(STAT/DIST)
(Reg)
(
x
ˆ)
4,861
Important!
• Regression coefficient, correlation coefficient, and estimated value calculations can
take considerable time when there are a large number of data items.
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