LabTalk Object Type:
The stat object provides for the following operations:
![]() |
Property | Access | Description |
---|---|---|
stat.adrsq | Read only numeric |
Adjust Coefficient of Determination (R squared). |
stat.chiSqrErr | Read/write numeric |
Multiply the error on the parameters with the reduced chi-square value. 1 = enable, 0 = disable. |
stat.cod | Read only numeric |
Coefficient of Determination (R squared). |
stat.confLevel | Read/write numeric |
Confidence level for calculating confidence and prediction limits. |
stat.errBarData$ | Read/write string |
Name of the error bar column to be used for calculating weights. |
stat.fitxData$ | Read/write string |
Name of the X column to be fitted. |
stat.fityData$ | Read/write string |
Name of the Y column to be fitted. |
stat.fValue | Read only numeric |
F test value (MSR/MSE). |
stat.lclData$ | Read/write string |
Name of the lower control line. |
stat.lplData$ | Read/write string |
Name of the lower prediction line. |
stat.makeX.fitnpts | Read/write numeric |
Number of points for the fitted curve. |
stat.makeX.fitX1 | Read/write numeric |
First X value to be used when making the FitX$ dataset with the MakeX() method. |
stat.makeX.fitX2 | Read/write numeric |
Last X value to be used when making the FitX$ dataset with the MakeX() method. |
stat.makeX.margin | Read/write numeric |
Percent of the raw data's range, of which to extend the fit X dataset beyond. |
stat.MSE | Read only numeric |
Mean sum of squares of residuals. |
stat.MSR | Read only numeric |
Mean sum of squares due to regression. |
stat.npts | Read only numeric |
Number of valid data points |
stat.pvalue | Read only numeric |
P-value for F test. |
stat.r | Read only numeric |
Correlation coefficient. |
stat.resData$ | Read only string |
Name of the residual column. |
stat.sd | Read only numeric |
Standard deviation of the fit. |
stat.SSE | Read only numeric |
Residual sum of squares. |
stat.SSR | Read only numeric |
Sum of squares due to regression. |
stat.SSTO | Read only numeric |
Total sum of squares. |
stat.uclData$ | Read/write string |
Name of the upper control line. |
stat.uplData$ | Read/write string |
Name of the upper prediction line. |
stat.wTotal | Read only numeric |
Total weight. |
stat.xMean | Read only numeric |
Mean value of the X column. |
stat.yMean | Read only numeric |
Mean value of the Y column |
Property | Access | Description |
---|---|---|
stat.lr.a | Read only numeric |
Intercept. |
stat.lr.ap | Read only numeric |
P-value for the t test of a. |
stat.lr.ase | Read only numeric |
Standard error of a. |
stat.lr.b | Read only numeric |
Slope. |
stat.lr.bp | Read only numeric |
P-value for the t-test of b. |
stat.lr.bse | Read only numeric |
Standard error of b. |
stat.lr.t | Read only numeric |
t value corresponding to the confidence level. |
Property | Access | Description |
---|---|---|
stat.pr.a,
stat.pr.b1, etc. |
Read only numeric |
Fitted parameters (a is the intercept). |
stat.pr.ap | Read only numeric |
P-value of the t-test for parameter a. |
stat.pr.ase, stat.pr.bse1, etc. |
Read only numeric |
Standard error of a and b[i]. |
stat.pr.bp1,
stat.pr.bp2, etc. |
Read only numeric |
P-values of the t-tests for parameters bi. |
stat.pr.order | Read/write numeric |
Order of the polynomial. |
stat.pr.t | Read only numeric |
t value according to the confidence level. |
Property | Access | Description |
---|---|---|
stat.mr.a | Read only numeric |
Intercept. |
stat.mr.ap | Read only numeric |
P-value of t-test for parameter a. |
stat.mr.ase | Read only numeric |
Intercept's error |
stat.mr.bestr2wks$ | Internal use only |
Not implemented in Origin. |
stat.mr.bi | Read only numeric |
Fitting parameters (i = 1 .. 9). |
stat.mr.bpi | Read only numeric |
P-values of t-test for parameters bi (i = 1 ..9). |
stat.mr.bsei | Read only numeric |
b[i]'s errors (i = 1 .. 9). |
stat.mr.NumX | Read only numeric |
The total number of X columns. |
stat.mr.pIn | Read only numeric |
Critical P-value to enter a variable in stepwise regression. |
stat.mr.pOut | Read only numeric |
Critical P-value to remove a variable in stepwise regression. |
stat.mr.t | Read only numeric |
t value according to confidence level. |
stat.mr.XDatai$ | Read/write string |
X column names (i = 1 ..9). |
stat.mr.YData$ | Read/write string |
Y column name |
Property | Access | Description |
---|---|---|
stat.DS.ad | -- |
Not currently implemented. |
stat.DS.CIL | Read only numeric |
Lower confidence limit about the mean (the percentage is set with stat.ds.confLev). |
stat.DS.CIU | Read only numeric |
Upper confidence limit about the mean (the percentage is set with stat.ds.confLev). |
stat.DS.cName1$ | -- |
Not currently implemented. |
stat.DS.confLev | Read/write numeric |
Confidence level (set to 0.95 by default). Set this property to load stat.ds.ciu and stat.ds.cil. |
stat.DS.data$ | Read/write string |
Name of dataset used to calculate descriptive statistics. |
stat.DS.geoMean |
Not currently implemented. |
|
stat.DS.interpolate | Read/write numeric |
Use interpolation when finding the quartiles/percentiles. 1 = enable, 0 = disable. |
stat.DS.kurt | Read only numeric |
Kurtosis of the data. Kurtosis measures the long-tailedness or peakedness of the distribution of a random variable relative to the normal or Gaussian distribution with the same mean and variance. |
stat.DS.max | Read only numeric |
Maximum of the data. |
stat.DS.mean | Read only numeric |
Mean value of the data. |
stat.DS.medCIL | -- |
Not currently implemented. Lower confidence limit about the median. |
stat.DS.medCIU | -- |
Not currently implemented. Lower confidence limit about the median. |
stat.DS.median | Read only numeric. |
Median of the data. |
stat.DS.min | Read only numeric |
Minimum of the data. |
stat.DS.missing | Read only numeric |
Number of missing values in the dataset. |
stat.DS.more | Read/write numeric |
Perform advanced statistics. 1 = enable, 0 = disable. |
stat.DS.percent | Read/write numeric |
The percentile to calculate when stat.ds() is performed. The percentile is loaded into stat.ds.percentile. |
stat.DS.percentile | Read only numeric |
Percentiles of the data. |
stat.DS.quart75 | Read only numeric |
The upper quartile (75th percentile). |
stat.DS.quartl25 | Read only numeric |
The lower quartile (25th percentile). |
stat.DS.quartl50 | Read only numeric |
The second quartile (50th percentile). |
stat.DS.range | Read only numeric |
Range of the data. |
stat.DS.sd | Read only numeric |
Standard deviation. |
stat.DS.se | Read only numeric |
Standard error of the mean. |
stat.DS.size | Read only numeric |
Number of data points in the dataset. |
stat.DS.skew | Read only numeric |
Skewness of the data. |
stat.DS.ssq | Read only numeric |
Sum of squares |
stat.DS.sum | Read only numeric |
Sum of the data. |
stat.DS.testNorm | -- |
Not currently implemented. |
stat.DS.var | Read only numeric |
Sample variance. |
Method | Description |
---|---|
stat.makeX() |
Make an X dataset in fitX$ that spans from FitX1 to FitX2. |
stat.name(CtrlBit, WksName_ColName, NewColNam1[, NewColNam2, ..., NewColNamn]) |
CtrlBit is either 1 or 0. When CtrlBit = 1, concatenate WksName_ColName to WksNameColName. This becomes the name of the new worksheet. Scan for already existing datasets: WksNameColName_NewColNam1, WksNameColName_NewColNam2, ..WksNameColName_NewColNamn. If a dataset already exists, then generate a new worksheet name (WksNameColNamen, where n = 1, 2, etc.) and scan again. When no duplicate names are found, set stat.name.worksheet$ to WksNameColName or WksNameColNamen. When CtrlBit = 0, concatenate WksName_ColName to WksNameColName. Do not search for previously existing datasets with identical names. Set stat.name.worksheet$ to WksNameColName. |
stat.reset() |
Reset all parameter values to their initial, unassigned values. |
Method | Description |
---|---|
stat.lr([z]) |
Linear regression for given datasets. When "z" is specified, the fitting line goes through the origin. For example : stat.data$ = %H_B; stat.errbardata$ = %H_C; stat.lr(); stat.lr.a = ; //Display intercept in Script window stat.lr.b = ; //Display slope in Script window |
Method | Description |
---|---|
stat.pr() |
Polynomial regression for given datasets. For example: stat.data$ = %H_B; stat.fitxdata$ = %H_D; //(optional) stat.fitydata$ = %H_E; //(optional) stat.pr(); |
Method | Description |
---|---|
stat.mr() |
Multiple regression for the given datasets.
stat.mr(); |
Method | Description |
---|---|
stat.DS() |
Descriptive and basic statistics for given dataset. |
This script performs a second order polynomial regression. It assumes that a Data1 worksheet is active and contains four columns: an X column with data, a Y column named B with data, an empty column named fitx, and an empty column named fity.
//Performs polynomial regression //%1 = order //%2 = name of dataset to fit (y variable) //%3 = name of dataset to store fitted x data //%4 = name of dataset to store fitted y data //%5 = number of points to create fitted curve [main] stat.reset(); //Reset the DLL stat.pr.order = %1; //order stat.data$ = %2; //dataset to fit stat.fitxdata$ = %3; //dataset to store fitted x values stat.fitYdata$ = %4; //dataset to store fitted y values stat.makeX.fitnpts = %5; //number of points of regression curve limit %2; //finds limiting values for the dataset to fit stat.makex.fitx1 = limit.xmin; stat.makex.fitx2 = limit.xmax; stat.makex(); stat.PR();
run.section(polynom.ogs, main, 2 data1_b data1_fitx data1_fity 100);