SAMPLING METHODSLEARNING OBJECTIVESWhat is research?Important Components of Empirical ResearchSAMPLINGSAMPLING……SAMPLING…….Slide 8Slide 9Types of SamplesProcessPopulation definitionPopulation definition…….SAMPLING FRAMEPROBABILITY SAMPLINGPROBABILITY SAMPLING…….NON PROBABILITY SAMPLINGNONPROBABILITY SAMPLING…….SIMPLE RANDOM SAMPLINGSIMPLE RANDOM SAMPLING……..REPLACEMENT OF SELECTED UNITSSYSTEMATIC SAMPLINGSYSTEMATIC SAMPLING……Slide 24STRATIFIED SAMPLINGSTRATIFIED SAMPLING……STRATIFIED SAMPLING…….POSTSTRATIFICATIONOVERSAMPLINGCLUSTER SAMPLINGCLUSTER SAMPLING…….Slide 32Slide 33Slide 34Difference Between Strata and ClustersMULTISTAGE SAMPLINGMULTISTAGE SAMPLING……..MULTI PHASE SAMPLINGMATCHED RANDOM SAMPLINGQUOTA SAMPLINGCONVENIENCE SAMPLINGCONVENIENCE SAMPLING…….Judgmental sampling or Purposive samplingPANEL SAMPLINGQuestions???What sampling method u recommend?Probability proportional to size samplingContd.Event samplingSlide 50contd.Dr. KANUPRIYA CHATURVEDI1SAMPLINGMETHODSLEARNING OBJECTIVES 2Learn the reasons for samplingDevelop an understanding about different sampling methodsDistinguish between probability & non probability samplingDiscuss the relative advantages & disadvantages of each sampling methodsWhat is research?3•“Scientific research is systematic, controlled, empirical, and critical investigation of natural phenomena guided by theory and hypotheses about the presumed relations among such phenomena.” –Kerlinger, 1986•Research is an organized and systematic way of finding answers to questionsImportant Components of Empirical Research4Problem statement, research questions, purposes, benefitsTheory, assumptions, background literatureVariables and hypothesesOperational definitions and measurementResearch design and methodologyInstrumentation, samplingData analysisConclusions, interpretations, recommendationsSAMPLING5A sample is “a smaller (but hopefully representative) collection of units from a population used to determine truths about that population” (Field, 2005)Why sample?Resources (time, money) and workloadGives results with known accuracy that can be calculated mathematicallyThe sampling frame is the list from which the potential respondents are drawn Registrar’s officeClass rostersMust assess sampling frame errorsSAMPLING……6What is your population of interest?To whom do you want to generalize your results?All doctorsSchool childrenIndiansWomen aged 15-45 yearsOtherCan you sample the entire population?SAMPLING…….73 factors that influence sample representative-nessSampling procedureSample sizeParticipation (response)When might you sample the entire population?When your population is very smallWhen you have extensive resourcesWhen you don’t expect a very high response8SAMPLING BREAKDOWNSAMPLING…….9TARGET POPULATIONSTUDY POPULATIONSAMPLETypes of Samples10Probability (Random) SamplesSimple random sampleSystematic random sampleStratified random sampleMultistage sampleMultiphase sampleCluster sampleNon-Probability SamplesConvenience samplePurposive sampleQuotaProcess 11The sampling process comprises several stages:Defining the population of concern Specifying a sampling frame, a set of items or events possible to measure Specifying a sampling method for selecting items or events from the frame Determining the sample size Implementing the sampling plan Sampling and data collecting Reviewing the sampling processPopulation definition12A population can be defined as including all people or items with the characteristic one wishes to understand. Because there is very rarely enough time or money to gather information from everyone or everything in a population, the goal becomes finding a representative sample (or subset) of that population.Population definition…….13Note also that the population from which the sample is drawn may not be the same as the population about which we actually want information. Often there is large but not complete overlap between these two groups due to frame issues etc . Sometimes they may be entirely separate - for instance, we might study rats in order to get a better understanding of human health, or we might study records from people born in 2008 in order to make predictions about people born in 2009.SAMPLING FRAME14In the most straightforward case, such as the sentencing of a batch of material from production (acceptance sampling by lots), it is possible to identify and measure every single item in the population and to include any one of them in our sample. However, in the more general case this is not possible. There is no way to identify all rats in the set of all rats. Where voting is not compulsory, there is no way to identify which people will actually vote at a forthcoming election (in advance of the election) As a remedy, we seek a sampling frame which has the property that we can identify every single element and include any in our sample .The sampling frame must be representative of the populationPROBABILITY SAMPLING15A probability sampling scheme is one in which every unit in the population has a chance (greater than zero) of being selected in the sample, and this probability can be accurately determined. . When every element in the population does have the same probability of selection, this is known as an 'equal probability of selection' (EPS) design. Such designs are also referred to as 'self-weighting' because all sampled units are given the same weight.PROBABILITY SAMPLING…….16Probability sampling includes: Simple Random Sampling, Systematic Sampling,Stratified Random Sampling, Cluster SamplingMultistage Sampling. Multiphase samplingNON PROBABILITY SAMPLING17Any sampling method where some elements of population have no chance of selection (these are sometimes referred to as 'out of coverage'/'undercovered'), or where the probability of selection can't be accurately determined. It involves the selection of elements based on assumptions regarding the population of interest, which forms the criteria for selection. Hence, because the selection of elements is nonrandom, nonprobability sampling not allows the estimation of sampling errors..Example: We visit every household in a given street, and interview the first person to answer the