Casio fx-CP400 User Manual page 133

k Regression graphs
Regression graphs of each of the paired-variable data can be drawn according to the model formulas under
"Regression types" below.
Linear regression graph
Regression types:
 Linear regression (LinearR) [Linear Reg] .............................................................. =
Linear regression uses the method of least squares to determine the equation that best fits your data
points, and returns values for the slope and -intercept. The graphic representation of this relationship is a
linear regression graph.
 Med-Med line (MedMed) [MedMed Line] ................................................................................... =
When you suspect that the data contains extreme values, you should use the Med-Med graph (which
is based on medians) in place of the linear regression graph. Med-Med graph is similar to the linear
regression graph, but it also minimizes the effects of extreme values.
 Quadratic regression (QuadR) [Quadratic Reg] ............................................................. =
 Cubic regression (CubicR) [Cubic Reg] ................................................................ =
 Quartic regression (QuartR) [Quartic Reg] ................................................. =
Quadratic, cubic, and quartic regression graphs use the method of least squares to draw a curve that
passes the vicinity of as many data points as possible. These graphs can be expressed as quadratic, cubic,
and quartic regression expressions.
 Logarithmic regression (LogR) [Logarithmic Reg] .................................................................... +
Logarithmic regression expresses as a logarithmic function of . The normal logarithmic regression
formula is = +
formula = + X.

b x
a e
Exponential regression (ExpR) [Exponential Reg]............................................................. =
Exponential regression can be used when is proportional to the exponential function of . The normal
exponential regression formula is =
. Next, if we say that Y = ln( ) and A = In( ), the formula corresponds to the linear regression formula Y
= A + .

a b x
Exponential regression (abExpR) [abExponential Reg] ........................................................ =
Exponential regression can be used when is proportional to the exponential function of . The normal
exponential regression formula in this case is =
get ln( ) = ln( ) + (ln( )) . Next, if we say that Y = ln( ), A = ln( ) and B = ln( ), the formula corresponds to
the linear regression formula Y = A + B .
 Power regression (PowerR) [Power Reg] ...................................................................................... =
Power regression can be used when y is proportional to the power of . The normal power regression
formula is = . If we obtain the logarithms of both sides, we get ln( ) = ln( ) +
that X = ln( ), Y = ln( ), and A = ln( ), the formula corresponds to the linear regression formula Y = A +
 Sinusoidal regression (SinR) [Sinusoidal Reg] ........................................................ =
Sinusoidal regression is best for data that repeats at a regular fixed interval over time.
Quadratic regression graph
ln( ). If we say that X = ln( ), then this formula corresponds to the linear regression
. If we obtain the logarithms of both sides, we get ln( ) = ln( ) +
. If we take the natural logarithms of both sides, we
Logistic regression graph
+ , =
3
+
4 3
+ +
ln( ). Next, if we say
sin(
Chapter 7: Statistics Application
+
+
2
+ +
2
+ +
2
+ +
ln( )
X.
+ ) +
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