A table becomes analytically reliable only when one row has a declared meaning and the key identifying that row is unique.

Base R; dplyr is optional for later joins.

unique key condition: anyDuplicated(key) = 0

1. Step 1Define every variable and unit.
2. Step 2Check assumptions and information timing.
3. Step 3Calculate, verify, and interpret in context.

Variable

Four dates, values, and ordered era labels.

Model choice

A join is trustworthy only after both sides' key relationships are checked.

Calculation

Four observations; date has Date class; era is an ordered two-level factor; duplicate-key count is zero.

Interpretation

The explicit date key and ordered era definition make sorting and grouping auditable.

Reasonableness check

Era boundaries are analyst choices and do not establish causal regimes.

The explicit date key and ordered era definition make sorting and grouping auditable. Limitation: Era boundaries are analyst choices and do not establish causal regimes.

Two observations appear in each declared era.

Run the self-contained starter code in the protected STATLAB R runner. The code prints an auditable result and avoids network or unrestricted file access.

Compare your result with the definition, units, and model assumptions—not only with a target number.

Complete these without looking at the selected solutions. More than one defensible program may exist.

These are compact solution routes. Confirm dimensions, units, and any changed modelling choices.

Build rectangular data, encode categories, parse dates, and validate keys before joins.

Name the assumption, evidence you would seek, and how the recommendation might change.

Reach 70% to complete the chapter. Explanations appear after submission.