Stratified sampling is ideal for?
ANSWER: (A) Heterogenous dataREF: Park 20th edition page 752Repeat from Primary DNB CET December 2008, December 2010SAMPLING METHODS: Simple random samplingSystematic samplingStratified samplingCluster sampling (AKA- Block sampling)PopulationHomogenousHomogenousHeterogenousHeterogenousUse of random number tableRequiredNot requiredRequiredRequiredMethodEach item in the population has the same probability of being selected as part of the sample as any other item.Evrery nth element from the list is selected as the sampleDivide population into homogenous subgroups. Random or systematic samples are then taken from each subgroup.Divide population into groups called clusters (heterogenous subgroups matching the population). A random sample is then taken from within one or more selected clusters.AdvantagesSimple, Easy to analysemore precise than simple random sampling as more evenly spread over populationMore precision because heterogeneous population is split into homogeneous strataReduced field costs,Applicable where no complete list of units is availableDisadvantagesif population heterogeneous estimates have large varianceif list has periodic arrangement, sample collected may not be an accurate representation of entire populationComplicated, Problems if strata not clearly definedComplicated,Clusters may not be representative of whole population
Heterogenous data
Homogenous data
Both
None
Statistical Tests