A table contains ten rows, each with a measurement. That does not necessarily mean ten different subjects were measured. The rows might represent ten readings from one subject, five readings from two subjects or another arrangement.
Identify the unit of each row
Look for a subject identifier and a measurement occasion. In a hypothetical classroom dataset, plant A might be measured on five days and plant B on the same five days. There are ten observations but only two plants.
Do not erase repeated identifiers automatically. Repetition may be an intended part of the design rather than a duplicate entry.
Match the count to the question
A question about the number of recorded readings differs from a question about the number of plants included. Write both counts when the distinction matters.
Repeated readings can reveal changes within a subject, but they do not magically create additional independent subjects. The appropriate analysis depends on the study design; a row count alone cannot establish it.
Add the distinction to your data notes
Record the row definition, identifier and time field before calculating summaries. If the documentation is unclear, ask for clarification rather than inferring the design from the spreadsheet’s appearance.
Our guide to checking a dataset before use provides the wider context. Knowing what a row represents is one of the simplest ways to prevent a precise calculation from answering the wrong question.