Linganisha mbinu

	Sampuli Tabakabaka ya Kulingana na Uwanja	Sampuli Iliyowekwa Ngazi
Nyanja	Metodolojia ya Dodoso	Metodolojia ya Dodoso
Familia	Process / pipeline	Process / pipeline
Mwaka wa asili	1934 (Neyman's stratified sampling theory); field applications throughout 20th century	1977
Mwanzilishi	Jerzy Neyman (stratified sampling theory); applied broadly in field survey practice	William G. Cochran
Aina	Probability sampling design	Probability-based survey sampling design
Chanzo asilia	Cochran, W. G. (1977). Sampling Techniques (3rd ed.). John Wiley & Sons. ISBN: 978-0471162407	Cochran, W. G. (1977). Sampling Techniques (3rd ed.). Wiley. ISBN: 978-0-471-16240-7
Majina mbadala	field stratified sampling, stratified field survey sampling, in-field stratified sampling, field survey stratification	Proportional Stratified Sampling, Optimal Allocation Sampling, Stratum-Based Sampling, Tabakalı Örnekleme
Zinazohusiana	6	2
Muhtasari	Field-based stratified sampling divides a geographically dispersed or heterogeneous target population into internally homogeneous subgroups (strata) defined by features observable in the field — such as land use type, habitat zone, administrative district, or community category — and then independently draws random samples from each stratum during on-site data collection. The approach combines the precision gains of stratification with the logistical realities of fieldwork, ensuring that every identifiable subgroup of the landscape or community is represented in the final data set.	Stratified sampling is a probability sampling design in which the target population is partitioned into non-overlapping, exhaustive subgroups called strata, and independent probability samples are drawn within each stratum. Formalized by William G. Cochran in Sampling Techniques (1977), the method exploits known population structure to reduce variance and guarantee representativeness of all major subgroups, making it a cornerstone of large-scale survey research and official statistics.