![]() If in addition to temperature we also measured humidity, then we’d have two measurements per observational unit but the number and type of observational units wouldn’t change. In this example, since we’re measuring temperature each week, we have one observational unit per city per week. In what follows, I’m assuming you have read the previous post and you are familiar with the temperature example I made there. However, if we’re following the patients over time, and we make those four measurements once every month for a year, then the observational units are the patient-months, i.e., we have one observational unit per patient each month. For example, if we’re studying a group of patients, and for each patient we measure height, weight, heart rate, and blood pressure, then the observational unit is the patient, and we are measuring four variables per observational unit. Importantly, multiple measurements can be performed on the same unit. An observational unit is the base unit on which measurements are done. In this case, it is important that we store them in separate tables, and that we know how to combine these tables for useful analyses.įirst, we need to figure out when we’re dealing with multiple observational units and when we are not. ![]() Frequently, however, we have data corresponding to multiple observational units. My previous post on tidy data didn’t at all touch on rule 3, “Each type of observational unit forms a table.” The example I gave had only one observational unit, the weekly temperature measurements.
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