{"id":56236,"date":"2018-04-13T02:46:57","date_gmt":"2018-04-13T09:46:57","guid":{"rendered":"https:\/\/www.questionpro.com\/blog\/?p=56236"},"modified":"2023-07-05T05:37:03","modified_gmt":"2023-07-05T05:37:03","slug":"cluster-sampling-vs-stratified-sampling","status":"publish","type":"post","link":"https:\/\/www.questionpro.com\/blog\/cluster-sampling-vs-stratified-sampling\/","title":{"rendered":"Cluster Sampling vs Stratified Sampling"},"content":{"rendered":"

Cluster Sampling and Stratified Sampling are <\/span>probability sampling<\/span><\/a> techniques with different approaches to create and analyze samples. \u00a0<\/span><\/p>\n

Select your respondents<\/strong><\/a><\/p>\n

Cluster Sampling<\/span><\/a> is a method where the target population is divided into multiple clusters. Some of these clusters are selected randomly for sampling or a second stage or multiple stage sampling is carried out to form the target sample. Depending on the number of steps followed to create the desired sample, cluster sampling is divided using a single-stage, two-stage or multiple stage sampling techniques<\/a>. This sampling method is extremely cost-effective as it requires minimum efforts in sample creation and also convenient to execute.<\/span><\/p>\n

LEARN ABOUT:<\/strong> Survey Sampling<\/a><\/p>\n

Stratified Sampling<\/span><\/a> is a probability sampling method, also called random quota sampling, where a large population is divided into unique, homogeneous strata and further, members from these strata are randomly selected to form a sample. Elements of each of the samples will be distinct which will give the entire population an equal opportunity to be a part of these samples. Segregation on the basis of age, religion, nationality, socioeconomic backgrounds, qualifications etc. can be done using this sampling technique.<\/span><\/p>\n

LEARN MORE: <\/strong>Population vs Sample<\/a><\/p>\n

In this blog, we will be discussing Cluster Sampling vs Stratified Sampling.<\/span><\/p>\n\n\n\n\n\n\n\n\n\n\n
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Factors for Comparison<\/b><\/p>\n<\/td>\n

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Cluster Sampling <\/b><\/p>\n<\/td>\n

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Stratified Sampling<\/b><\/p>\n<\/td>\n<\/tr>\n

Definition<\/span><\/td>\nMembers of this sample are chosen from naturally divided groups called clusters, by randomly selecting elements to be a part of the sample. <\/span><\/td>\nMembers of this sample are randomly chosen from non-overlapping, homogeneous strata.<\/span><\/td>\n<\/tr>\n
Purpose<\/span><\/td>\nCost reduction and increased efficiency. <\/span><\/td>\nEnhanced precision and population depiction. <\/span><\/td>\n<\/tr>\n
Sample selection<\/span><\/td>\nSelection of the sample is done by randomly selected clusters and including all the members from these clusters. \u00a0<\/span><\/td>\nSelection of the sample is done by randomly selecting members from various formed strata.<\/span><\/td>\n<\/tr>\n
Selection of elements that form a Sample<\/span><\/td>\nConjointly<\/span><\/td>\nDistinctively <\/span><\/td>\n<\/tr>\n
Division type<\/span><\/td>\nNaturally formed<\/span><\/td>\nDepends on the researcher<\/span><\/td>\n<\/tr>\n
Heterogeneity <\/span><\/td>\nInternally, with the clusters <\/span><\/td>\nExternally, between various strata<\/span><\/td>\n<\/tr>\n
Homogeneity<\/span><\/td>\nExternally, between various clusters<\/span><\/td>\nInternally, with the strata<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Cluster Sampling – Key Points:<\/b><\/p>\n