Skip Nav

Stratified sampling

Uses of Stratified Random Sampling

❶For example, you have 3 strata with , and population sizes respectively.

Stratified random sampling

Navigation menu
This article is a part of the guide:
The Advantages of Sampling

The American Journal of Clinical Nutrition in 2004 published a systematic review of meta-analyses and clinical trials on dietary supplements for weight loss by complementary medicine researchers at the Universities of Exeter and Plymouth.

None of the over-the-counter weight loss aids worked, including garcinia cambogia. Late in 2010 the peer-reviewed Journal of Obesity published a meta-analysis of studies testing the garcinia as a weight loss aid. Of the 23 trials they identified, 12 were methodologically sound enough to include in their analysis.

Resource Links:

Main Topics

Privacy Policy

Stratified sampling is a probability sampling method and a form of random sampling in which the population is divided into two or more groups (strata) according to one or more common attributes. Stratified random sampling intends to guarantee that the sample represents specific sub-groups or strata.

Privacy FAQs

Stratified sampling is a probability sampling technique wherein the researcher divides the entire population into different subgroups or strata, then randomly selects the final subjects proportionally from the different strata.

About Our Ads

Stratified random sampling is a method of sampling that involves the division of a population into smaller groups known as strata. In stratified random sampling or stratification, the strata are formed based on members' shared attributes or characteristics. A stratified sample is one that ensures that subgroups (strata) of a given population are each adequately represented within the whole sample population of a research study. For example, one might divide a sample of adults into subgroups by age, like , , , , and 60 and above. To.

Cookie Info

Stratified random sampling is a method of sampling that involves the division of a population into smaller groups known as strata. In stratified random sampling, or stratification, the strata are formed based on members' shared attributes or characteristics. Stratified random sampling is a type of probability sampling using which a research organization can branch off the entire population into multiple non-overlapping, homogeneous groups (strata) and randomly choose final members from the various strata for research which reduces cost and improves.