Report STATISTICA COM availability, version and executable path. Run this first if STATISTICA operations fail.

List every analysis procedure exposed by STATISTICA (id + name) that can be driven with run_analysis.

Open a .sta/.stw file and report case count, variable count and every variable (index, short name, clean name, long name/formula, type, measurement level, missing code).

Read variable values. Numeric columns are read vectorized; text columns as strings. Missing values are returned as null.

List the sheets inside a .sta/.stw file (index, name, size) without loading variable data.

Introspect a STATISTICA analysis dialog before driving it: lists every settable property and callable method, plus known enum constants. Use it to build a run_analysis request.

Overwrite whole variables in a spreadsheet. Numeric columns require exactly one value per case; missing values may be null. Text columns accept per-row strings (shorter arrays leave the rest untouched). Changes are only persisted if save is given.

Assign a formula to a variable (STATISTICA keeps it in the variable long name) and recompute it, e.g. formula "=v9*v10". The result values are returned for inspection. Use attach=true to write into the running STATISTICA window.

Append new empty variables to a spreadsheet. type: 0=numeric, 1=text, 2=integer, 3=byte.

Rename variables and/or change their long names, keyed by current variable name or index.

Delete an inclusive range of variables by index or name.

Resize a spreadsheet. Growing adds empty cases/variables; shrinking discards the excess.

Read (and optionally set) case names / text labels for the rows of a spreadsheet. When names is given they are written (one per case, starting at case 1).

Sort a spreadsheet in place by one or more keys (case names move with their rows). order may be a single value or one per key: 0/asc or 1/desc.

Keep only the rows matching a condition and drop the rest (all columns are rewritten). Supports numeric and text comparisons; missing values can be matched with op "missing".

Recode the values of one variable using a mapping (old value -> new value), optionally sending every unlisted value to default. Missing values are preserved unless missing is given.

Set the measurement level of a variable (auto/continuous/categorical/ordinal). STATISTICA uses it to treat the variable as a factor or a covariate in analysis.

Attach or clear text labels for the numeric values of a variable. labels maps a numeric value to a label string or an object {label, description}; clear removes existing labels first.

Export a sheet to CSV using the STATISTICA built-in CSV writer.

Save a sheet to a new file. Extension selects the format (.sta, .stw, .csv, .xlsx).

Import a delimited text file or an Excel workbook into STATISTICA and optionally save it as .sta.

Launch STATISTICA visibly, optionally build a graph/analysis result, then capture the main window to a PNG/JPG image for a report. Content is prepared while hidden, then the window is shown and captured.

Open an analysis module dialog in the running STATISTICA window and capture the actual setup panel to an image (Time Series/Forecasting, Transformations tabs, etc.). Use run:true to advance to the second-level panel.

Launch a visible STATISTICA window (optionally opening a file) and leave it running. Subsequent calls with attach:true edit this same window — no repeated start/stop of the application.

Fast descriptive statistics computed in Node from data read through COM (N, missing, mean, sd, se, min, q1, median, q3, max, sum). Missing values are honoured using each variable's declared missing code.

Descriptive statistics computed by the STATISTICA engine itself (Basic Statistics module), including ones the JS shortcut does not provide.

Pearson correlation matrix computed by the STATISTICA Basic Statistics module.

Frequency tables and histograms computed by the STATISTICA Basic Statistics module.

Multiple linear regression via STATISTICA General Regression Models. The first predictor list entry is the dependent variable? No: dependent is the outcome and predictors are the regressors.

Student t-tests via the STATISTICA Basic Statistics module. kind=single tests means against a constant; kind=dependent runs paired comparisons over the listed variables (pairs).

Build a STATISTICA graph and optionally export it to an image file. variables uses the module syntax, typically "x | y". properties sets additional dialog options (e.g. GraphType, FitType, ShowRawDataPoints). Common modules: 11003 2D Scatterplots, 11012 2D Line Plots, 11002 2D Histograms, 11010 2D Box Plots, 11021 3D Sequential, 11032 3D Surface.

Time Series / Forecasting module. procedure is one of: descriptives, autocorrelation, partial_autocorrelation, cross_correlation, arima, spectral, smoothing, shift, exponential_smoothing, differencing, seasonal_decomposition. autocorrelation/partial_autocorrelation/spectral/smoothing/differencing/descriptives operate on a single series.

Analysis of variance via STATISTICA General Linear Models (module 4100 / ANOVA). dependent is the outcome; between lists factor/covariate effects. Returns the ANOVA table (UnivariateResults) and parameter estimates.

Hierarchical cluster analysis (module 2201). variables are the variables to cluster; returns cluster membership, the amalgamation schedule and descriptive statistics.

Factor analysis / principal components (module 2101). Extraction method defaults to PrincipalComponents; factors sets the requested number of factors. Returns eigenvalues, loadings and communalities.

Build lagged series products for a time series: for lags 1..lags it creates variables Lag1..LagK holding x(t)*x(t-lag) (correlation products), optionally smoothed with a moving average, and returns their preview. Use mode "shift" for plain lagged series.

Fit an ordinary least-squares line of y on x (x defaults to the case number) and write the fitted values to a new variable, so the trend can be plotted next to the data (a scriptable substitute for the interactive graph fit).

Execute STATISTICA BASIC (SVB) source code (or a .svb file) with the opened spreadsheet as ActiveSpreadsheet, then optionally save the result. Use it for custom recurrent models (DWLS/Lowess/EWPR) supplied as SVB macros.

Normality diagnostics via the Basic Statistics module: descriptive summary plus Shapiro-Wilk W and Kolmogorov-Smirnov/Lilliefors tests and a histogram.

Compute the lag-m correlation product x(t)*x(t-lag) of a series, smooth it with a centered moving average, and append it as a named column to a target sheet (builds the Month + Lag1..LagK matrix step by step).

Run ANY STATISTICA analysis by executing an ordered list of steps against its dialog. Each step is one of: {"set": {PropertyName: value}} (set dialog properties), {"call": "MethodName", "args": [...]} (invoke a dialog method, e.g. ARIMAAndAutocorrelationFunctions), {"run": true} (execute the analysis), {"result": "Summary"} (read a result document/table after the run), {"saveGraph": "C:\out\plot.png", "result": "Graphs"} (export a graph document to an image; .png/.jpg/.emf). Results are returned as tables, arrays or document handles. Use describe_analysis to discover property and method names.