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E-19
(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.
fx-82/85/350ES PLUS: (SETUP)A(STAT)(OFF)
fx-95ES PLUS: (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 + 2357.532lnx
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.
STATSTAT
33
STAT
FIX
STAT
FIX
44
C
20


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