পদ্ধতির তুলনা করুন

	Spot Observation Sampling	Behavioral Observation Coding
ক্ষেত্র	Anthropology	Anthropology
পরিবার	Process / pipeline	Process / pipeline
উদ্ভবের বছর	1984	1974
প্রবর্তক	Time-allocation tradition in cultural anthropology (synthesized by Gross)	Behavioral sampling tradition (Altmann), adapted to anthropology (Bernard)
ধরন	Instantaneous sampling procedure for estimating time allocation	Systematic procedure for sampling and coding observed behavior
মৌলিক উৎস	Gross, D. R. (1984). Time allocation: a tool for the study of cultural behavior. Annual Review of Anthropology, 13, 519–558.	Altmann, J. (1974). Observational study of behavior: sampling methods. Behaviour, 49(3–4), 227–267.
অপর নাম	Spot Check Sampling, Instantaneous Spot Observation, Random Spot Checks, Spot Sampling	Behavior Coding, Systematic Observation Coding, Behavioral Sampling and Coding, Observational Coding
সম্পর্কিত	4	4
সারসংক্ষেপ	Spot observation sampling is a time-allocation technique in which an observer arrives at randomly chosen moments and records, instantaneously, exactly what each visible person is doing at that instant — not what they were doing before or after. Because the moments are sampled at random across the daily and seasonal round, the proportion of spot observations that fall in a given activity is an unbiased estimate of the proportion of time people spend in that activity. It turns a scatter of brief snapshots into a quantitative budget of how a community allocates its waking hours.	Behavioral observation coding is the systematic practice of recording who does what, when, by applying an explicit sampling rule and a predefined coding scheme to observed behaviour. Rather than jotting impressions, the observer commits in advance to a rule — focal-individual, scan, ad libitum, or continuous sampling — and to a list of mutually defined behaviour categories, so that records are reproducible and comparable. Because two trained observers should code the same scene the same way, the method also requires measuring inter-observer reliability before the data are trusted.