Stratification of target populations is extremely common in survey sampling. Simple random sampling is the most recognized probability sam-pling procedure. Sampling Theory | Chapter 4 | Stratified Sampling | Shalabh, IIT Kanpur Page 1 Chapter 4 Stratified Sampling An important objective in any estimation problem is to obtain an estimator of a population parameter which can take care of the salient features of the population. If we can assume the strata are sampled independently across strata, then based on the following; Systematic random sampling, Stratified types of sampling, Cluster sampling, Multi-stage sampling, Area sampling, Types of probability random sampling Systematic sampling Thus, in systematic sampling only the first unit is selected randomly and the remaining units of the sample are to be selected by •For instance, information may be available on the geographical location of the area, e.g. Please note that some file types are incompatible with some mobile and tablet devices. Stratified random sampling is a method of sampling that involves the division of a population into smaller groups known as strata. Copy and paste the following HTML into your website. Stratified random sampling is a method of sampling that involves the division of a population into smaller sub-groups known as strata. Random sampling is a form of probabilistic sampling where every person or item in the population has the same opportunity to be included into the selected few (Taherdoost, 2016). View Stratified_Random_Sampling_78c6aa5498e19f027941ea5120112a4f.pdf from ACTUARIAL SC204/0039 at Meru University College of Science and Technology (MUCST). Quota sampling is a non-probability sampling technique in which researchers look for specific qualities or traits in their respondents, and then take a sample that is in proportion to a population of interest. 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The principal properties of the estimate y 11 are outlined in the following theorems. Simple Random Sampling • Each element in the population has an equal probability of selection AND each combination of elements has an equal probability of selection • Names drawn out of a hat • Random numbers to select elements from an ordered list. if it is an inner city, a suburban or a rural area. The samples selected from the various strata are then combined into a single sample. They are also usually the easiest designs to implement. These two designs highlight a trade‐offs inherent in selecting a sampling design: to select Simple random sampling with replacement (SRSWR): SRSWR is a method of selection of n units out of the N units one by one such that at each stage of selection, each unit has an equal chance of being selected, i.e., 1/ .N. Please choose from an option shown below. Stratified random sampling is a method for sampling from a population whereby the population is divided into subgroups and units are randomly selected from the subgroups. Following stratification, a sample is selected from each stratum, often through simple random sampling. 3 STRATIFIED SIMPLE RANDOM SAMPLING Suppose the population is partitioned into disjoint sets of sampling units called strata. Like simple random sampling, systematic sampling is a type of probability sampling where each element in the population has a known and equal probability of being Sign into your Profile to find your Reading Lists and Saved Searches. Sampling Theory| Chapter 4 | Stratified Sampling | Shalabh, IIT Kanpur Page 1 Chapter 4 Stratified Sampling An important objective in any estimation problem is to obtain an estimator of a population parameter which can take care of the salient features of the population. 11aeorem S.l. sample is time-saving. Stratified sampling techniques are often used when designing business, government, and social science surveys; therefore, it is important for researchers to understand how to design and analyze stratified samples. if it is an inner city, a suburban or a rural area. To obtain a stratified sample, members of a population are first divided into nonoverlapping subgroups of units called strata.

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