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In a cluster sample, researchers divide subjects into strata (like cities, for example), randomly select a few strata (draw the names of a few cities from a hat) and sample every subject in those strata (question everyone in that city.)
A significant disadvantage is that you may select strata that completely overlook a feature relevant to your study.
If your study polled "What is the importance of agriculture to our country's economy?" and you questioned people from New York, Chicago, Detroit, and Los Angeles, your data may be bias because it does not include opinion from more rural areas.
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How do multistage sampling applies to real life situation?
Multistage sampling is a form of cluster sampling where instead of using the entire cluster, random samples from each cluster are used. This is typically used when doing opinion polls or surveys.
How do you get sample using universal sampling technique?
try researching about total enumeration technique... it's the other name for universal sampling technique ^_^ Good luck..
Describe a situation where you would consider using cluster sampling?
At the Brother in Parhump NV.
What is Biased sampling?
Using sample that does not match the population
What does Sampling Theorem refer to?
Sampling Theorum is related to signal processing and telecommunications. Sampling is the process of converting a signal into a numeric sequence. The sampling theorum gives you a rule using DT signals to transmit or receive information accurately.
What is the Difference between random and systematic sampling?
Random sampling is picking a subject at random. Systematic sampling is using a pattern to pick subjects, I.e. picking every third person.
Why you are using sampling theorem in communication systems?
sampling is a one type of process use for converting into analog signal to digital signal.
What is the method of estimation using a representative section of a whole?
sampling
What is a method of estimation using a representative section of the whole?
sampling
What statistical tests can I use on data collected from quota samples?
You can use statistical tests appropriate for categorical data, such as chi-square tests or Fisher's exact test for associations between variables. For continuous data, you can use t-tests or non-parametric tests like Mann-Whitney U test or Kruskal-Wallis test. It's important to consider the limitations of quota sampling in interpreting the results.
How do you overcome limitations of stacks in polygon filling?
You overcome limitations of the stack in polygon filling, or in any other algorithm, far that matter, but using an iterative technique, rather than a recursive technique. Recursion is quite useful, and can simplify algorithm design. Polygon filling, however, is a class of algorithm can potentially have a very deep recursion depth. This causes stress on the stack, hence the need for iteration.
When every member of a population has the chance of being selected based on the probability or frequency of its representation in that population you are using which type of sampling?
Systematic sampling
