Observation (observare, to watch) is the act of monitoring and recording something or someone. It can be done passively, by simply taking in information that is already present, or actively, by seeking out specific stimuli and noting one’s reaction to them. Observation is a fundamental scientific method used to collect data about the natural world. It is also an important tool in many other fields, such as medicine, psychology, sociology, education, and engineering.
There are several different types of observation: direct observation (also called participant observation), indirect observation, structured observation, and unstructured observation. Direct observation involves observing subjects while they are engaged in their natural behavior; this type of observation is often used in field studies of animals or humans. Indirect observation entails observing subjects indirectly, usually via some sort of recording device; this could include anything from security cameras to baby monitors. Structured observations are those in which the observer has a specific protocol to follow; these are often used in lab experiments or clinical trials. Unstructured observations are more casual; the observer simply takes note of whatever they deem interesting or important.
Observations can be qualitative or quantitative. Qualitative observations rely on the observer’s senses and judgment to record what they see; these data are typically descriptive (e.g., “the sky was blue”) rather than numerical (e..g,”the temperature was 72 degrees”). Quantitative observations use some form of measuring device to obtain objective data that can be expressed numerically (e..g,”the patient’s heart rate was 78 beats per minute”). Both types of data are important for understanding a phenomenon under study.
The quality of an observational study depends on several factors: the observers must be trained properly so that their measurements are accurate and reliable; the conditions under which observations are made should be controlled as much as possible; and finally, there must be enough subjects observed so that any trends or patterns that emerge from the data are statistically significant. Poorly designed observational studies can produce results that are misleading or outright wrong.