Variables

The nodes of your causal graph — the things you measure.

Every causal graph is a set of variables connected by edges. A variable is a measurable quantity in your domain.

Variable types

• Continuous — real-valued (temperature, price, latency).
• Discrete — a finite set of categories (department, status, tier).
• Binary — true/false (churned, approved, flagged).
• Count — non-negative integers (visits, retries, staff on shift).

Nora picks a sensible default statistical treatment per type but you can override.

Creating a variable

From the graph canvas:

• Click + Variable and fill in:
  • Name — how you’ll refer to it (blood_pressure_systolic, refund_processed).
  • Display label — human-readable version shown on the node.
  • Type — continuous / discrete / binary / count.
  • Unit — for continuous (mmHg, USD, ms).
  • Description — one line. Shown in tooltips and used by extraction.
  • Values — for discrete, the allowed categories.

Modeling advice

• Prefer measurable variables. “Customer satisfaction” is too vague; “NPS score” or “days-to-resolution” is measurable.
• One variable per concept. Don’t merge “temperature” and “pressure” into one node.
• Name variables in the direction of measurement. refund_rate not no_refund. Positive framing avoids double-negatives when reasoning.
• Split composite variables. “Cost” splits into labor_cost, materials_cost, etc. — clearer edges downstream.

Attributes

Every variable can carry metadata:

• Range — expected min/max for continuous.
• Reference values — normal, warning, critical.
• Source — where the variable was measured or estimated (link to a document or dataset).
• Confidence — how confident you are in this variable’s role in your model.

Metadata surfaces in analysis and in verification (e.g., “the Agent claimed X = 200, but X’s range is 0-50”).

Grouping

Group related variables into clusters (visual only — doesn’t affect causal semantics):

• Drag variables into a group.
• Give the group a name and color.
• Collapse to hide detail; expand to work with individuals.

Great for large graphs — 50+ variables becomes navigable when grouped by subsystem.

Renaming

Renaming a variable updates every edge, every attached document, and every stored analysis. No stale references.

Deleting

Deleting a variable removes all incoming and outgoing edges. Nora warns you and shows the cascade. Deleted variables can be restored within 30 days from the graph history.

Bulk import

Import variables from a CSV:

name,type,unit,description
temperature,continuous,celsius,ambient temperature at sensor A
status,discrete,,pipeline status (ok/warn/err)

Then use extraction to propose edges among them (see Extract from documents).