Describe the difference between a probability sample and a nonprobability sample. The difference between nonprobability and probability sampling is that nonprobability sampling does not involve random selection and probability sampling does. Does that mean that nonprobability samples aren’t representative of the population? Not necessarily. But it does mean that nonprobability samples cannot depend upon the rationale of probability theory. At least with a probabilistic sample, we know the odds or probability that we have represented the population well. We are able to estimate confidence intervals for the statistic. With nonprobability samples, we may or may not represent the population well, and it will often be hard for us to know how well we’ve done so. In general, researchers prefer probabilistic or random sampling methods over nonprobabilistic ones, and consider them to be more accurate and rigorous.
However, in applied social research there may be circumstances where it is not feasible, practical or theoretically sensible to do random sampling. Here, we consider a wide range of nonprobabilistic alternatives. 4. In what types of situations is conducting a census more appropriate than sampling? When is sampling more appropriate than taking a census? Actually, a census typically uses sampling. However, I think I understand what you are asking. I think you are asking when is sampling to derive an estimated population more appropriate than taking a full count.
The Indian census is a good example. Sampling is used to take smaller group counts to mathematically infer something about a larger group. Sampling’s positive characteristics are that it is faster, cheaper and mathematically more accurate in counting large groups. The downside is that it is subject to sample bias if sampling is not done correctly and is less accurate for small groups.
This contrasts to a full count, where everything is individually verified. Full count has the benefits of being more accurate in small groups but has the disadvantages of being slow, inaccurate for large groups and expensive.
The key differential is that sampling tries to estimate the total population within a given standard deviation on both the positive and negative side. The full count almost always has a negative bias because it is a “positive audit”. Let’s say you are counting rural individuals in Kerala. You literally have to have a person go to every single place to find people in Kerala, make sure you haven’t double counted them as they move around and make sure that you didn’t miss anyone. That’s an impossible task. Now, if you took a sample of a smaller rural space, say 10% of Kerala, 0.5% in 20 different spots around Kerala, you could infer something about the whole 100%.
For this reason, I believe the Indian census is far, far underestimating the total population in India. 5. Comment on the following sampling design:
a. By using questionnaire they take people attention to give some support to what that they want to do. When people start to get interesting to your activity, you can start to make some proposal to get financial support base on result of that sample of questionnaire. b. Using sample from every tenth credit card holder the department store will get a fresh sample for gaining costumers draw. They can using that result from sample to make some change of management and a new way to sell the product to take attention of buyer to come to the store. c. The questionnaire that they use will give some result of the favorite motorcycle in this year or every year. They can use it to make some graph to track down the type and a brand of motorcycle that can using be top brand of sales of the years. I think they make a good move to take a questionnaire from every dealers. d. I think by giving incentive for the first thousand responses he assume that he will get a fast response and a fast result of the questionnaire that he want.
He can get all of it just one day and he can get more that thousand responses because people will think he just make one of the first thousand responses although they don’t. e. I think the best way to get a good sample is using different group people, so we can combine all of the thought about the researching. By using the diffrent opinion from some people. f. I think to change system to a new system, we must pick sample from user that accustomed to the system. So when we change the way the system giong, user that will using it will not get difficult to using the new one. 6. When would a researcher use a judgment, or purposive, sample?
Purposive sampling is used in cases where the specialty of an authority can select a more representative sample that can bring more accurate results than by using other probability sampling techniques. The process involves nothing but purposely handpicking individuals from the population based on the authority’s or the researcher’s knowledge and judgment. Judgmental sampling design is usually used when a limited number of individuals possess the trait of interest. It is the only viable sampling technique in obtaining information from a very specific group of people. It is also possible to use judgmental sampling if the researcher knows a reliable professional or authority that he thinks is capable of assembling a representative sample.