Long format data is described as:

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Multiple Choice

Long format data is described as:

Explanation:
Long format stores data so that each observation is a separate row, with the measured score in a single column and additional columns describing the observation (such as the subject, time point, or condition). This means one subject can have multiple rows—one per time point or condition—so the same entity appears multiple times, each with its own score in that one column. That description precisely fits the option: scores are kept in one column, and rows encode the combination of attributes for those scores. In contrast, wide format would put each score in its own column, giving one row per entity. Aggregating across time points into a single mean per entity reduces the data to a high-level summary rather than showing each observation, and storing each score in a separate column is another form of wide formatting.

Long format stores data so that each observation is a separate row, with the measured score in a single column and additional columns describing the observation (such as the subject, time point, or condition). This means one subject can have multiple rows—one per time point or condition—so the same entity appears multiple times, each with its own score in that one column. That description precisely fits the option: scores are kept in one column, and rows encode the combination of attributes for those scores.

In contrast, wide format would put each score in its own column, giving one row per entity. Aggregating across time points into a single mean per entity reduces the data to a high-level summary rather than showing each observation, and storing each score in a separate column is another form of wide formatting.

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