Texas Instruments TI-84 - Manual (Page 314)

Chapter 12: Statistics 311
PwrReg (power regression) fits the model equation y=ax
b
to the data using a least-
squares fit and transformed values ln(x) and ln(y). It displays values for a and b ; when
DiagnosticOn is set, it also displays values for r
2
and r .
PwrReg [ Xlistname,Ylistname,freqlist,regequ ]
Logistic— Logistic— Logistic— Logistic—c/ c/ c/ c/(1+a (1+a (1+a (1+a
…
e ee e
-bx
))))
Logistic fits the model equation y=c/(1+a …e
L bx
) to the data using an iterative least-squares
fit. It displays values for a , b , and c .
Logistic [ Xlistname,Ylistname,freqlist,regequ ]
SinReg—a sin(bx+c)+d SinReg—a sin(bx+c)+d SinReg—a sin(bx+c)+d SinReg—a sin(bx+c)+d
SinReg (sinusoidal regression) fits the model equation y=a sin(bx+c)+d to the data using
an iterative least-squares fit. It displays values for a , b , c , and d . At least four data points
are required. At least two data points per cycle are required in order to avoid aliased
frequency estimates.
SinReg [ iterations , Xlistname , Ylistname , period , regequ ]
iterations is the maximum number of times the algorithm will iterate to find a solution. The
value for iterations can be an integer ‚ 1 and  16; if not specified, the default is 3. The
algorithm may find a solution before iterations is reached. Typically, larger values for
iterations result in longer execution times and better accuracy for SinReg , and vice versa.
A period guess is optional. If you do not specify period , the difference between time values
in Xlistname must be equal and the time values must be ordered in ascending sequential