2 SAMPLINGProcedure by which some members of a given population are selected as representatives of the entire population.
3 UNIVERSEthe larger group from which individuals are selected to participate in a studySAMPLEthe representatives selected for a study whose characteristics exemplify the larger group from which they were selected
4 PURPOSE OF SAMPLING To gather data about the population in order to make an inference that can be generalized to the populationPOPULATIONINFERENCESAMPLE
5 Process Of Sampling Define the Population Develop Sampling Frame Select a Sampling MethodDetermine Sample SizeExecute the Sampling Process
6 The Sampling Process Define the Population Develop Sampling Frame Select a Sampling MethodDetermine the Sample SizeExecute the Sampling Process
7 Sampling and representativeness SampleSamplingPopulationTarget PopulationTarget Population Sampling Population Sample
8 Sampling Techniques Fixed Attributes Vs Vs Sequential Variables ProbabilityVsNon-probabilitysampling
9 NON-PROBABILITY SAMPLING Every element in the target population or universe [sampling frame] has equal probability of being chosen in the sample for the survey being conducted.Scientific, operationally convenient and simple in theory.Results may be generalized.NON-PROBABILITY SAMPLINGEvery element in the universe [sampling frame] does not have equal probability of being chosen in the sample.Operationally convenient and simple in theory.Results may not be generalized.
10 CLASSIFICATION OF SAMPLING TECHNIQUES Sampling MethodsProbability Sampling MethodsSimple Random SamplingStratified Random SamplingSystematic Random SamplingMultistage Random SamplingCluster SamplingArea SamplingNon-probability Sampling MethodsConvenience SamplingJudgment SamplingQuota SamplingOther Sampling Methods
11 SIMPLE RANDOM SAMPLING Simple random sampling is a method of probability sampling in which every unit has an equal non zero chance of being selected for the sample.Methods of selecting random sample:Lottery MethodTables of Random Numbers
12 STRATIFIED RANDOM SAMPLING Stratified random sampling is a method of probability sampling in which the population is divided into different subgroups and samples are selected from each of them.Steps:-All units of population are divided into different stratas in accordance with their characteristics.Using random sampling, sample items are selected from each stratum.
13 Systematic Random Sampling or Quasi-Random Sampling Systematic random sampling is a method of probability sampling in which the defined target population is ordered and the 1st unit of sample is selected at random and rest of the sample is selected according to position using a skip interval (every Kth item)K = NnWhere, K = Sampling/ Skip intervalN = Universe/ Population Sizen = Sample Size
14 MULTISTAGE RANDOM SAMPLING Used in large scale investigationsFirst stage- preparation of large sized sampling unitsRandomly selecting a certain numberSecond stage- Another list prepared from themSub-samples drawn by random sampling
15 CLUSTER SAMPLING Steps :- The process of randomly selecting intact groups, not individuals, within the defined population sharing similar characteristicsSteps :-Defined population is divided into number of mutually exclusive and collectively exhaustive subgroups or clustersSelect an independent simple random sample of clusters.
16 Area SamplingOne special type of cluster sampling is called area sampling, where pieces of geographical areas such as districts, housing blocks or townships are selected.Area sampling could be one-stage, two-stage, or multi-stage.Generally used by Govt. agencies and agricultural statistics.
18 Convenience samplingthe process of including whoever happens to be available at the time…called “accidental” or “haphazard” sampling.
19 Purposive samplingthe process whereby the researcher selects a sample based on experience or knowledge of the group to be sampled…called “judgment” sampling
20 Quota samplingthe process whereby a researcher gathers data from individuals possessing identified characteristics and quotas
21 Other Non-probability Sampling Methods Intensity sampling: selecting participants whopermit study of different levels of the research topicHomogeneous sampling: selecting participants whoare very similar in experience, perspective, or outlookCriterion sampling: selecting all casesthat meet some pre-defined characteristicSnowball sampling relies upon respondentreferrals of others with like characteristics
22 Factors to Consider in Sample Design Research objectivesDegree of accuracyResourcesTime frameKnowledge oftarget populationResearch scopeStatistical analysis needs