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Slide 1 Sampling in Qualitative and Quantitative Research A practical how-to 1 Key themes A famous sampling mistake Quantitative assumptions in sampling Qualitative assumptions in sampling Types of sampling Ethnographic sampling Interview sampling Content analysis sampling How many? 2 A famous sampling mistake 3 A famous sampling mistake Thatâs Truman They only asked rich, white people with telephones whoâd they vote for. Sadly, they published their mistake 4 Even with proper samplingâ¦beware! ââ¦predicting behavior on the basis of knowledge of attitude is a very hazardous venture.â Meaning, predicting social behavior is often misguided. Keep that in mind! 5 What exactly IS a âsampleâ? 6 What exactly IS a âsampleâ? A subset of the population, selected by either âprobabilityâ or ânon-probabilityâ methods. If you have a âprobability sampleâ you simply know the likelihood of any member of the population being included (not necessarily that it is ârandom.â 7 I want to know what causes something else. What do quant researchers worry about? I really spend a lot of time wondering how to measure things. I wonder how small patterns generalize to big patterns. I want to make sure others can repeat my findings. 8 Assumptions of quantitative sampling We want to generalize to the population. Random events are predictable. Thereforeâ¦ We can compare random events to our results. Probability sampling is the best approach. 9 I want to see the world through the eyes of my respondents. What do qual researchers worry about? I want to describe the context in a lot of detail. I want to show how social change occurs. Iâm interested in how things come to be. I really want my research approach to be flexible and able to change. 10 Assumptions of qualitative sampling Social actors are not predictable like objects. Randomized events are irrelevant to social life. Probability sampling is expensive and inefficient. Thereforeâ¦ Non-probability sampling is the best approach. 11 Types of samples 12 Simple Random Sample Get a list or âsampling frameâ This is the hard part! It must not systematically exclude anyone. Remember the famous sampling mistake? Generate random numbers Select one person per random number Systematic Random Sample Select a random number, which will be known as k Get a list of people, or observe a flow of people (e.g., pedestrians on a corner) Select every kth person Careful that there is no systematic rhythm to the flow or list of people. If every 4th person on the list is, say, ârichâ or âseniorâ or some other consistent pattern, avoid this method Stratified Random Sample Separate your population into groups or âstrataâ Do either a simple random sample or systematic random sample from there Note you must know easily what the âstrataâ are before attempting this If your sampling frame is sorted by, say, school district, then youâre able to use this method Multi-stage Cluster Sample Get a list of âclusters,â e.g., branches of a company Randomly sample clusters from that list Have a list of, say, 10 branches Randomly sample people within those branches This method is complex and expensive! The Convenience Sample Find some people that are easy to find 17 The Snowball Sample Find a few people that are relevant to your topic. Ask them to refer you to more of them. 18 The Quota Sample Determine what the population looks like in terms of specific qualities. Create âquotasâ based on those qualities. Select people for each quota. 19 The Theoretical Sample 20 What about generalizing? âOur findings have a margin of error of + or - 4%, 19 times out of 20.â âThe average man is 35% more likely to choose this option over the average woman.â 21 Proviso in non-probability sampling: no generalizing âOur findings have a margin of error of + or - 4%, 19 times out of 20.â âThe average man is 35% more likely to choose this option over the average woman.â 22 Ethnographers sampleâ¦ People Places Contexts Times Events 23 Interviewers sampleâ¦ People Places Times 24 Content analysts sampleâ¦ Media Dates 25 How many? Qualitative researchers seek âsaturationâ âHow manyâ isnât the issue. Do you understand the phenomenon? Have you learned enough? Mere numbers are irrelevant. You want âverstehnâ or deep understanding Quantitative researchers seek statistical validity Can you safely generalize to the population? Have you systematically excluded anyone? (See the âfamous sampling mistakeâ!) 26 Improving Response Rates Personalize the invitation Offer money -- no strings attached! 27 Copernicus Consulting Design research and strategy http://www.copernicusconsulting.net