Daxaben N MehtaSmt.S.C.U.Shah Home Science and C.U.Shah Arts & Commerce Mahila College Wadhwancity
Define population (N) to be sampledQuantitative assumptions in samplingQualitative assumptions in samplingTypes of samplingEthnographic samplingInterview samplingContent analysis samplingHow many? Determine sample size (n)A famous sampling mistakeControl for bias and error
The process of selecting a number of individuals for a study in such a way that the individuals represent the larger group from which they were selected
Sample……the representatives selected for a study whose characteristics exemplify the larger group from which they were selected
Population……the larger group from which individuals are selected to participate in a study
To gather data about the population in order to make an inference that can be generalized to the population
Identify the group of interest and its characteristics to which the findings of the study will be generalized …called the “target” population (the ideal selection)…oftentimes the “accessible” or “available” population must be used (the realistic selection)
A subset of the population, selected by either “probability” or “non- probability” methods. If you have a “probability sample” you simply know the likelihood of anymember of the population being included (not necessarily that it is “random.”
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We want to generalizeto the population. Random events are predictable. We can compare random events to our Therefore… results. Probability sampling is the best approach.
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Social actors are notpredictable like objects. Randomized events are irrelevant to social life. Probability sampling is Therefore… expensive and inefficient. Non-probability sampling is the best approach.
1 Get a list or “sampling frame” This is the hard part! It must not systematically exclude anyone. Remember the famous sampling mistake?2 Generate random numbers3 Select one person per random number
advantages… easy to conduct strategy requires minimum knowledge of the population to be sampled
disadvantages… need names of all population members may over- represent or under- estimate sample members there is difficulty in reaching all selected in the sample
1 Select a random number, which will be known as k2 Get a list of people, or observe a flow of people (e.g., pedestrians on a corner)3 Select every kthperson Careful that there is no systematic rhythm to the flow or list of people. If every 4th person on the list is, say, “rich” or “senior” or some other consistent pattern, avoid this method
disadvantages… all members of the population do not have an equal chance of being selected the Kth person may be related to a periodical order in the population list, producing unrepresentativeness in the sample
1 Separate your population into groups or “strata”2 Do either a simple random sample or systematic random sample from there Note you must know easily what the “strata” are before attempting this If your sampling frame is sorted by, say, school district, then you’re able to use this method
advantages……more precise sample…can be used for both proportions and stratification sampling…sample represents the desired strata
disadvantages……need names of all population members…there is difficulty in reaching all selected in the sample…researcher must have names of all populations
1 Get a list of “clusters,” e.g., branches of a company2 Randomly sample clusters from that list3 Have a list of, say, 10 branches4 Randomly sample people within those branches This method is complex and expensive!
advantages……efficient…researcher doesn’t need names of all population members…reduces travel to site…useful for educational research
disadvantages……fewer sampling points make it less like that the sample is representative
Convenience samplingthe process of including whoever happens to be available at the time …called “accidental” or “haphazard” sampling Find some people that are easy to find
disadvantages……difficulty in determining how much of the effect (dependent variable) results from the cause (independent variable)
Purposive samplingthe process whereby the researcher selects a sample based on experience or knowledge of the group to be sampled …called “judgment ” sampling
1. Find a few people that are relevant to your topic.2. Ask them to refer you to more of them.
disadvantages……potential for inaccuracy in the researcher’s criteria and resulting sample selections
Quota samplingthe process whereby a researcher gathers data from individuals possessing identified characteristics and quotas
1 Determine what the population looks like in terms of specific qualities.2 Create “quotas” based on those qualities.3 Select people for each quota.4 the process whereby a researcher gathers data from individuals possessing identified characteristics and quotas
disadvantages……people who are less accessible (more difficult to contact, more reluctant to participate) are under- represented
“The average man is 35% more likely to“Our findings have a choose this option over margin of error of + the average woman.” or - 4%, 19 times out of 20.”
…qualitative research is characterized by in-depth inquiry, immersion in a setting, emphasis on context, concern with participants’ perspectives, and description of a single setting, not generalization to many settings
…because samples need to be small and many potential participants are unwilling to undergo the demands of participation, most qualitative research samples are purposive
…representativeness is secondary to the quality of the participants’ ability to provide the desired information about self and setting
1. Intensity sampling: selecting participants who permit study of different levels of the research topic2. Homogeneous sampling: selecting participants who are very similar in experience, perspective, or outlook
3. Criterion sampling: selecting all cases that meet some pre-defined characteristic4. Snowball sampling: selecting a few individuals who can identify other individuals who can identify still other individuals who might be good participants for a study
5. Random purposive sampling: with a small sample, selecting by random means participants who were purposively selected and are too numerous to include all in the study
Qualitative researchers seek “saturation” “How many” isn’t the issue. Do you understand the phenomenon? Have you learned enough? Mere numbers are irrelevant. You want “verstehn” or deep understanding Quantitative researchers seek statistical validity Can you safely generalize to the population? Have you systematically excluded anyone?
The size of the sample influences both the representativeness of the sample and the statistical analysis of the data …larger samples are more likely to detect a difference between different groups …smaller samples are more likely not to be representative
1. The larger the population size, the smaller the percentage of the population required to get a representative sample2. For smaller samples (N ‹ 100), there is little point in sampling. Survey the entire population.
3. If the population size is around 500 (give or take 100), 50% should be sampled.4. If the population size is around 1500, 20% should be sampled.5. Beyond a certain point (N = 5000), the population size is almost irrelevant and a sample size of 400 may be adequate.
1. Sampling error2. Sampling bias …which threaten to render a study’s findings invalid
That’sTruman They only asked rich, white people with telephones who’d they vote for. Sadly, they published their mistake
“…predicting behavior onthe basis of knowledge of attitude is a very hazardous venture.” Meaning, predicting social behavior is often misguided. Keep that in mind!
Sampling error……the chance and random variation in variables that occurs when any sample is selected from the population…sampling error is to be expected
…to avoid sampling error, a census of the entire population must be taken…to control for sampling error, researchers use various sampling methods
Sampling bias……nonrandom differences, generally the fault of the researcher, which cause the sample is over-represent individuals or groups within the population and which lead to invalid findings…sources of sampling bias include the use of volunteers and available groups
Be aware of the sources of sampling bias and identify how to avoid it Decide whether the bias is so severe that the results of the study will be seriously affected In the final report, document awareness of bias, rationale for proceeding, and potential effects