HP 50g HP 50g_user's manual_English_HDPSG49AEM8.pdf - Page 160

Fitting data to a function y = f(x), Fit data..

Page 160 highlights

Fitting data to a function y = f(x) The program 3. Fit data.., available as option number 3 in the STAT menu, can be used to fit linear, logarithmic, exponential, and power functions to data sets (x, y), stored in columns of the ΣDAT matrix. For this application, you need to have at least two columns in your ΣDAT variable. For example, to fit a linear relationship to the data shown in the table below: xy 0 0.5 1 2.3 2 3.6 3 6.7 4 7.2 5 11 • First, enter the two columns of data into variable ΣDAT by using the Matrix Writer, and function STOΣ. • To access the program 3. Fit data.., use the following keystrokes OK@@@. The input form will show the current ΣDAT, already loaded. If needed, change your set up screen to the following parameters for a linear fitting: • To obtain the data fitting press @@OK@@. The output from this program, shown below for our particular data set, consists of the following three lines in RPN mode: 3: '0.195238095238 + 2.00857242857*X' 2: Correlation: 0.983781424465 1: Covariance: 7.03 Page 16-5

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Page 16-5
Fitting data to a function y = f(x)
The program
3. Fit data..
, available as option number 3 in the STAT
menu, can be used to fit linear, logarithmic, exponential, and power
functions to data sets (x, y), stored in columns of the
Σ
DAT matrix.
For this
application, you need to have at least two columns in your
Σ
DAT variable.
For example, to fit a linear relationship to the data shown in the table
below:
First, enter the two columns of data into variable
Σ
DAT by using the
Matrix Writer, and function STO
Σ
.
To access the program
3. Fit data..
, use the following keystrokes:
‚Ù˜˜
@@@OK@@@
.
The input form will show the current
Σ
DAT,
already loaded.
If needed, change your set up screen to the following
parameters for a linear fitting:
To obtain the data fitting press
@@OK@@
.
The output from this program,
shown below for our particular data set, consists of the following three
lines in RPN mode:
3: '0.195238095238 + 2.00857242857*X'
2: Correlation: 0.983781424465
1: Covariance: 7.03
x
y
0
0.5
1
2.3
2
3.6
3
6.7
4
7.2
5
11