sampling dr majed el-farra1 selecting samples chapter 6
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sampling Dr Majed El-Farra 1
Selecting samples
Chapter 6
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Meeting objectives
1. Understand the need and importance of sampling in business and management research.
2. Be aware of a range of probability and non-probability sampling techniques.
3. Be aware of how to select the write research sample.
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Sample provide alternatives to census when: importance:
1. It would be impractical to survey the entire population.
2. You have limited budget to survey the entire population.
3. Limited time available.4. You need quick results.
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Sampling techniques
Probability or representative sampling Non-probability or judgmental
sampling. Probability sampling: the chance or
probability of each case being selected from the population is known and is usually equal for all cases.
Non-probability sampling: the opposite.
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Probability sampling
It is associated with survey-based research where you need to make inferences/conclusions from your sample about a population to answer your research question or to meet your objectives.
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Steps of designing probability sampling.
1. Identify a suitable sampling frame based on your research question.
2. Decide on a suitable sample size.3. Select the most appropriate sampling
technique and select the sample.4. Check that the sample is
representative of the population.
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Identifying a suitable sampling frame The sampling frame for probability sample
is a complete list of all the population cases.
Examples on sampling frame: teamwork activity:
1. Leadership style of Gaza’s managers in the private sector.
2. Constraints of scientific research at IUG faculty of commerce: Academics viewpoint.
3. Internal constraints of industrial development in the Gaza Strip.
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Factors govern sample size
1. The confidence you need in data.2. The margin of error that you can
tolerate.3. The type of analysis that you are
going to undertake.4. The size of total population.
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Views on Sample size The economists
believe that sample size of 30 would be relevant to many cases.
Researchers normally work to a 95% level certainty. The margin error is 5%.
Pop. 5% margin eror
100 79
150 108
300 168
500 21
1000 278
2000 322
5000 357
10000 370
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Reasons for non-response
1. Refusal to respond.2. Ineligibility to respond. Does not
meet research requirements.3. Inability to locate respondent.4. Respondent located but unable
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Select the most appropriate sampling technique and select the sample.
Simple sample Systematic Stratified sample Cluster Multi-stage
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Simple random sample Select the sample at a random from the
sampling frame. How to select:1. Number each of the cases in your sampling
frame (0,1,2,..).2. Select cases using random number. Methods: sampling with replacement and
without replacement. Random selection reduce bias. Random sample is used when you can list
the entire population.
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Systematic sampling Selecting the sample at regular intervals
from the sampling frame. Selection steps:1. Number each of the cases with unique
number.2. Select the first case using a random
number.3. Calculate the sampling fraction: sample
size/population size4. Select the subsequent cases
systematically.
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Stratifies random sampling
steps1. You divide the population into 2 or
more strata based on one or a number of attributes.
2. Random sample is drawn (simple or systematic) from each strata.
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Cluster sampling You divide the population into
discrete/separate groups prior to sampling. The sampling frame is the complete list of
clusters rather than complete list of cases within the population.
You select few clusters. Used when you undertake an interview
based research and you have limited resources.
Ex. Conducting research on the behavior in of visa card clients in the Gaza Strip.
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Multi-stage sampling or multi-stage cluster sampling Used when the population geographically dispersed,
and face to face contact is needed. Steps: Phase one:1. Choose sampling frame of relevant discrete groups.2. Number each group with a unique number (0,1)3. Select randomly a small sample of relevant discrete
groups using some form of random sampling Phase two:From the relevant discrete groups choose a sampling
frame and continue the steps as mentioned above. Phase three: repeat phase 2 if necessary.
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Non-probability sampling In the exploratory stages non-probability
sampling may be the most practical, using pilot survey.
Sampling techniques:1. Quota2. Purposive3. Snowball4. Self-selection5. convenience
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Non-probability sampling Quota Alternative to stratified sample. When is it used?1. Cost constrained2. Data needed quickly Steps of designing quota sampling:1. Divide the population into specific groups.2. Calculate a quota for each group based on relevant and
available data.3. Collect data from defined numbers. Quota is used in market research surveys, usually include
measures of age, gender, socioeconomic status. It can often produce a good results, but you cannot
measure the level of certainty.
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Non-probability sampling Purposive or judgmental:Usually used with small samples, or used with
researchers following the grounded theory. Purposive sampling strategies:1. Focuses on extreme cases e.g., most success
companies. This enables you understand more typical cases.
2. Heterogeneous or maximum variation sampling. You should identify the diverse characteristics prior selection.
3. Homogeneous: focus on one particular subgroup, all sample members are similar.
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Non-probability sampling SnowballUsed when it is difficult to identify members of
desired population. Respondents are most likely identify other potential respondents.
There is a problem in representativeness.e.g. knowing how CEO succeeded and reach
such high rank.We start with one CEO and he helps in identify
others to meet and others identify others and so one.
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Non-probability sampling
Self-selectionWhen you allow individuals to identify
their desire/willingness to take part in the research by informing them with your research problem and objectives. Data will be collected from individuals who express their interest to participate.
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Non-probability sampling
Convenience/ haphazard sampling.Involves selecting haphazardly those
cases that are easiest to obtain. Example: standing at the uni. Campus
and ask students you meet to fill a questionnaire and you keep doing so tell you get the sample size.
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Group work
Simple sample Systematic Stratified sample Cluster Multi-stageTwo groups will work on these samples. They
should draw working examples how to use these samples in reality. Theses samples will be divided between the groups.
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Group work
Sampling techniques:1. Quota2. Purposive3. Snowball4. Self-selection5. ConvenienceTwo groups will work on these samples. They
should draw working examples how to use these samples in reality. Theses samples will be divided between the groups.
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