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Chapter 10: Statistics & Regression Calculations
06 Rg_x
4
Rg_x
4
(list name for x, list name for y [, frequency list] [,
equation name to store])
Finds the regression curve using the fourth degree polynomial.
(quadratic regression)
Formula: y = ax
4
+ bx
3
+ cx
2
+ dx + e
Parameters: a, b, c, d, e, R
2
07 Rg_ln Rg_ln
(list name for x, list name for y [, frequency list] [,
equation name to store])
Finds the regression curve using the natural logarithm. (natural
logarithm regression)
Formula: y = a
+ b ln x
Parameters: a, b, r, r
2
08 Rg_log Rg_log
(list name for x, list name for y [, frequency list] [,
equation name to store])
Finds the regression curve using the common logarithm. (com-
mon logarithm regression)
Formula: y = a + b log x
Parameters: a, b, r, r
2
09 Rg_ab
x
Rg_ab
x
(list name for x, list name for y [, frequency list] [,
equation name to store])
Finds the regression curve using the exponential function.
(exponential regression)
Formula: y = ab
x
Parameters: a, b, r, r
2
10 Rg_ae
bx
Rg_ae
bx
(list name for x, list name for y [, frequency list] [,
equation name to store])
Finds the regression curve using the Euler exponential function.
(Euler exponential regression)
Formula: y = ae^bx
Parameters: a, b, r, r
2