Activity sampling is an approach to data collection where an observer takes notes of all activities taking place at given intervals, rather than making continuous observations. It may also be known as work sampling in some settings. This statistical technique can allow for detailed evaluation of a setting like a workplace with a high level of efficiency. Fewer workers are necessary to collect the data, and it will be less expensive to analyze because there will be less of it.
People can take two approaches to activity sampling. One approach uses fixed intervals. For example, someone observing a construction site might check every half hour. The observer would note all activities on the site, the level of progress, and any pertinent details. In random sampling, observers check at varying intervals to record data, usually with the use of a tool like a number generator to make the sampling as random as possible.
It is possible to use calculations to determine the confidence interval for the purpose of evaluating the validity of the data. The more samples the better, but the sampling can reach a point where adding more samples wouldn't provide very much utility, and would add expense. Researchers can determine the optimal number of samples to collect on the basis of the study parameters and setting. This allows them to determine the level of authority provided by study results.
One use for activity sampling is in efficiency studies. A company may want to know how efficient its employees are and can use this information to identify problem areas. For example, activity sampling may show that one station slows up an assembly line, as the observer notes a stack of items waiting for attention during each sample period. Likewise, the sampling might illustrate communication breakdowns that slow a process, ranging from making a product to providing a service to customers.
This can also be used in studies of working conditions, health care services, and other activities. In any situation where people perform work over an extended period of time, activity sampling can provide detailed information about the nature, quality, and efficiency of that work. Observers may use a variety of techniques to avoid biasing the results, such as actually working on a factory floor like a regular employee while making observations. The presence of an obvious observer recording data might skew behaviors.
