E-23
(SETUP)
A
(STAT)
(ON)
(STAT)
(1-VAR)
1
2
3
4
5
AC
1
2
3
2
(STAT)
(Var)
(
M
)
(STAT)
(Var)
(
S
x
)
Results:
Mean: 3
Population Standard Deviation: 1.154700538
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)
A
(STAT)
(OFF)
(SETUP)
(Fix)
(STAT)
(A+BX)
20
110
200
290
AC
3150
7310
8800
9310
(STAT)
(Reg)
(r)
(STAT)
(Type)
(In X)
(STAT)
(Reg)
(r)
(STAT)
(Reg)
(A)
(STAT)
(Reg)
(B)
Results:
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.
To determine the estimate value for
y
when
x
= 160 in the
regression formula produced by logarithmic regression of the data
in
3
. Specify Fix 3 for the result. (Perform the following operation
after completing the operations in
3
.)
160
(STAT)
(Reg)
(
L
)
Result:
8106.898
Important:
Regression coefficient, correlation coefficient, and estimated
value calculations can take considerable time when there are a large number
of data items.
3
3
STAT
FIX
STAT
FIX
4
4