Documentation / Experimental Data Analyst /

Experimental Data Analyst—Quick Reference

Using available options, Experimental Data Analyst (EDA) is capable of very sophisticated analysis. This guide briefly reviews the use of common EDA routines for simple analysis tasks.

Data Formats

Dependent variable only:

Independent and dependent variable:

Explicit errors in the dependent variable:

Explicit errors in both coordinates:

Further information: §1.2

Importing and Exporting Data from/to an ASCII File

Further information: §2.1 and §2.2

Propagation of Errors of Precision

Using *WithError Functions

For data of the form:

then use:

More generally, if the data are related by:

then use:

Further information: §3.3.1

Using Datum and Data Constructs

For data of the form:

or:

then:

Further information: §3.3.1.1

Fitting to a Straight Line

Fit to:

with:

Further information: §4.2

Fitting to a Polynomial

Fit to:

with:

Further information: §4.2

Fitting to an Exponential

Fit to:

with:

Further information: §8.4.2

Fit to Gaussian Spectra

Fit to:

with:

Further information: §8.4.1

Fit to Lorentzian Spectra

Fit to:

with:

Further information: §8.4.1

Fit to a General Model

Fit to:

where x is the independent variable, is the i-th parameter with initial value with:

Further information: §5.1

Data Massage

To smooth out noise in a bivariate dataset:

Further information: §6.1.1, §6.1.2

To do a nonparametric fit with a "loess" technique using polynomials of order order:

Further information: §6.1.3

To fill missing data points in multivariate data:

Further information: §6.1.6

Robust Fit to a Line

Fit to:

using robust techniques with:

or:

Further information: §7.1.1 and §7.1.2

Robust Fitting to a Polynomial

Fit to:

using robust techniques with:

Further information: §7.1.2

Miscellaneous Graphics

Generalized ListPlot:

Further information: §8.1.1

Histogram:

Further information: §8.1.2

BoxPlot:

Further information: §8.1.3

Log plot:

Further information: §8.1.4

Log-log plot:

Further information: §8.1.4

Miscellaneous

To find peaks in a dataset:

Further information: §8.3