Sampling

1. What is the difference between probability and nonprobability samples? Explain in your own words and give examples of each type of sample.


Probability sample:

• You have a complete sampling frame. You have contact information for the entire population.
• You can select a random sample from your population. Since all persons (or “units”) have an equal chance of being selected for your survey, you can randomly select participants without missing entire portions of your audience.
• You can generalize your results from a random sample. With this data collection method and a decent response rate, you can extrapolate your results to the entire population.
• Can be more expensive and time-consuming than convenience or purposive sampling.

Non-probability sample:

• Used when there isn’t an exhaustive population list available. Some units are unable to be selected, therefore you have no way of knowing the size and effect of sampling error (missed persons, unequal representation, etc.).
• Not random.
• Can be effective when trying to generate ideas and getting feedback, but you cannot generalize your results to an entire population with a high level of confidence. Quota samples (males and females, etc.) are an example.
• More convenient and less costly, but doesn’t hold up to expectations of probability theory.

2.What are the advantages of choosing a probability sample in your research?


Non-probability sampling:
-the method is easy to use, but that advantage is greatly offset by the presence of bias.
-it can deliver accurate results when the population is homogeneous.
- the reduced cost and time involved in acquiring the sample.
- Insures some degree of representativeness of all the strata in the population


The following are the basic advantages of probability sampling methods:
•Probability sampling does not depend upon the existence of detailed information about the universe for its effectiveness.
•Probability sampling provides estimates which are essentially unbiased and have measurable precision.
•It is possible to evaluate the relative efficiency various sample designs only when probability sampling is used
• Easy and convenient


3.If you want to do a random cluster sampling of 10 people out of this entire class, how should you go about it?


I estimate my class will have 100 students. First, I’ll cluster my sample by region. I may have 40 chinese, 30 Malays, 25 Indians and 5 from other country. I select Chinese and Indians. From the two groups I selected. I cluster them by different states for example Selangor, Perak, Johor and Penang. I may select penang and Selangor. After that, I’ll determine a list of the topic from the selction and finally I random my sample from the last cluster.


4. If you want to do a random stratified sampling of 10 people – 7 females, 3 males – out of this entire class, how should you go about it?

We will be using disproportionate stratified sampling method. This method is used to oversample or over-represent a particular stratum. The approach is used because that stratum is considered important for marketing, advertising, or other similar reasons. For example, Pantene is promoting a new shampoo that just emerged in the market, the shampoo is mainly used by girls but also can be used by men.


5. What is ‘sampling error’, in your understanding?

An error in a statistical analysis arising from the unrepresentative of the sample taken.