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Chapter 2

Workspace Basics

SCCalc is organized around stable work areas:

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Workspace Basics

Main Areas

SCCalc is organized around stable work areas:

  • Data Editor: enter, paste, inspect, edit, sort, and review rows and columns.
  • Variable View: review names, labels, types, measurement levels, value labels, and missing-value conventions.
  • Analysis dialogs: select variables, set procedure options, and run analyses.
  • Results: inspect tables, charts, model summaries, warnings, and export-ready output.
  • SCL tools: write, run, debug, and reuse repeatable analysis workflows.
  • Help: search task help, tutorials, shortcuts, support guidance, and manuals.

The menu bar is the primary command surface. Toolbar controls and contextual panes support common tasks, but the menus give the most complete view of what the app can do.

Projects And Files

Project files keep the working dataset, metadata, notes, and analysis context together. Use File -> New Project, File -> Open Project, File -> Save Project, and File -> Save Project As for project-level work.

Because SCCalc is sandboxed on macOS, file access is granted through system open and save panels. When importing, saving, or exporting, choose the file or destination folder through the macOS panel so SCCalc receives permission to read or write there.

Use File -> Duplicate Project before risky restructuring, large transformations, or exploratory analysis. A duplicate gives you a clean recovery point without changing the original project.

Data And Variable Views

Use Data Editor for row-and-column inspection. It is the best place to spot empty rows, obvious typing errors, unexpected category labels, outliers, and columns that imported as text.

Use Variable View before inferential analysis. Confirm:

  • Variable names are unique and stable.
  • Labels describe the construct without exposing private context.
  • Numeric variables imported as numeric values.
  • Categorical variables have the expected categories.
  • Measurement levels match the procedure you plan to run.
  • Missing-value conventions are documented.

If analysis dialogs reject a variable or produce unexpected warnings, return to Variable View and check type, measurement level, and missing-data settings first.

Use these menus for the main workflow:

  • File: project creation, opening, saving, import, export, printing, and file security.
  • View: zoom, toolbar and inspector visibility, spreadsheet and variable views, formula bar, sheet tabs, status bar, and freeze panes.
  • Data: variable properties, named ranges, generated datasets, sorting, restructuring, merging, aggregation, filtering, weighting, transformations, cleaning, validation, and exploration.
  • Analysis: statistical procedure families, workflow builder, and Run Again.
  • Results: results browser, reports, diagrams, display options, result export, output documents, pinned results, and verification.
  • SCL: SCL IDE, scripts, highlighted code export, script execution, navigator, debug area, inspector, command palette, snippets, and SCL shortcuts.
  • Help: manuals, tutorials, keyboard shortcuts, SCL references, sample data, feedback, support, community links, and privacy policy.

Working Safely

Before major transformations, save the project. For work that must be auditable, keep an unchanged copy of the original source data in a secure location outside the working project. Record any transformation choices that affect results, including filters, computed variables, reverse-coded items, weighting, split files, imputation, and deleted cases.

For analysis sessions that may be repeated, move the workflow into an SCL script once the manual dialog steps are stable. A script makes it easier to re-run the same import, preparation, analysis, and export steps after new data arrives.

Confidential Workspaces

Treat the workspace as confidential whenever it contains real participant, customer, student, patient, financial, institutional, proprietary, or unpublished research data. Before sharing screenshots, project files, SCL scripts, or exported output, remove:

  • Names, IDs, email addresses, account numbers, and direct identifiers.
  • Rare categories, locations, timestamps, and other indirect identifiers.
  • Raw free-text responses, comments, and notes.
  • Private file paths, organization names, project names, and unpublished study labels.
  • Passwords, tokens, secrets, and internal service URLs.
  • Results that are not approved for disclosure.

If you are unsure whether something is confidential, do not share it. Describe the workflow and error first, then prepare a sample or synthetic reproduction if support needs more detail.