What are the advantages of using a simple random sample to study a larger population? Simple random sampling is a method used to cull a smaller sample size from a larger population and use it to research and make generalizations about the larger group. It is one of several methods statisticians and researchers use to extract a sample from a larger population; other methods include stratified random sampling and probability sampling.
However, there are obviously times when one sampling method is preferred over the other. The following explanations add some clarification about when to use which method.
Stratified sampling would be preferred over cluster sampling, particularly if the questions of interest are affected by time zone.
For example the percentage of people watching a live sporting event on television might be highly affected by the time zone they are in. Cluster sampling really works best when there are a reasonable number of clusters relative to the entire population.
In this case, selecting 2 clusters from 4 possible clusters really does not provide much advantage over simple random sampling. Either stratified sampling or cluster sampling could be used. It would depend on what questions are being asked. For instance, consider the question "Do you agree or disagree that you receive adequate attention from the team of doctors at the Sports Medicine Clinic when injured?
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|Social Research Methods - Knowledge Base - Probability Sampling||With a lottery method, each member of the population is assigned a number, after which numbers are selected at random.|
|Simple random sampling||In order to have a random selection method, you must set up some process or procedure that assures that the different units in your population have equal probabilities of being chosen. Humans have long practiced various forms of random selection, such as picking a name out of a hat, or choosing the short straw.|
In contrast, if the question of interest is "Do you agree or disagree that weather affects your performance during an athletic event? Consequently, stratified sampling would be preferred. Cluster sampling would probably be better than stratified sampling if each individual elementary school appropriately represents the entire population as in aschool district where students from throughout the district can attend any school.
Stratified sampling could be used if the elementary schools had very different locations and served only their local neighborhood i. Again, the questions of interest would affect which sampling method should be used.
The most common method of carrying out a poll today is using Random Digit Dialing in which a machine random dials phone numbers. Some polls go even farther and have a machine conduct the interview itself rather than just dialing the number! Such "robo call polls" can be very biased because they have extremely low response rates most people don't like speaking to a machine and because federal law prevents such calls to cell phones.
Since the people who have landline phone service tend to be older than people who have cell phone service only, another potential source of bias is introduced. National polling organizations that use random digit dialing in conducting interviewer based polls are very careful to match the number of landline versus cell phones to the population they are trying to survey.
Non-probability Sampling The following sampling methods that are listed in your text are types of non-probability sampling that should be avoided: In your textbook, the two types of non-probability samples listed above are called "sampling disasters.
The article provides great insight into how major polls are conducted. When you are finished reading this article you may want to go to the Gallup Poll Web site, https: It is important to be mindful of margin or error as discussed in this article.
We all need to remember that public opinion on a given topic cannot be appropriately measured with one question that is only asked on one poll. Such results only provide a snapshot at that moment under certain conditions. The concept of repeating procedures over different conditions and times leads to more valuable and durable results.
Within this section of the Gallup article, there is also an error: In 5 of those surveys, the confidence interval would not contain the population percent.Simple random sampling is a method used to cull a smaller sample size from a larger population and use it to research and make generalizations about the larger group.
It is one of several methods.
Simple random sampling. Simple random sampling is a type of probability sampling technique [see our article, Probability sampling, if you do not know what probability sampling is].
With the simple random sample, there is an equal chance (probability) of selecting each unit from the population being studied when creating your sample [see .
Sample Size Calculator. This Sample Size Calculator is presented as a public service of Creative Research Systems survey yunusemremert.com can use it to determine how many people you need to interview in order to get results that reflect the target population as precisely as needed.
Simple random sampling (also referred to as random sampling) is the purest and the most straightforward probability sampling strategy. It is also the most popular method for choosing a sample among population for a wide range of purposes. Simple random sampling explained.
Buy Survey Research & Sampling Edition (Statistical Associates "Blue Book" Series Book 7): Read 4 Kindle Store Reviews - yunusemremert.com RESEARCH RANDOMIZER RESEARCH RANDOMIZER RANDOM SAMPLING AND RANDOM ASSIGNMENT MADE EASY! RANDOM SAMPLING AND RANDOM ASSIGNMENT MADE EASY! Research Randomizer is a free resource for researchers and students in need of a quick way to generate random numbers or assign . Nov 10, · A survey is a valuable assessment tool in which a sample is selected and information from the sample can then be generalized to a larger population. Surveying has been likened to taste-testing soup – a few spoonfuls tell what the whole pot tastes like. The key to .
Imagine that a researcher wants to understand more about the career goals of students at a single university. Let's say that the university has roughly 10, students. Simple random sampling is a very basic type of sampling method and can easily be a component of a more complex sampling method.
The main attribute of this sampling method is that every sample has the same probability of being chosen.