0
1) Simple random sampling
2) Systematic sampling
3) Stratified sampling
4) Cluster sampling
5) Probability proportional to size sampling
6) Matched random sampling
7) Quota sampling
8) Convenience sampling
9) Line-intercept sampling
10) Panel sampling
Wiki User
∙ 13y ago
Add your answer:
Earn +20 pts
What is the difference between probability sampling and simple random sampling?
Simple random sampling = A process of selecting subjects in such a way that each member of the population has an equal likelihood of being selected; you can throw all your subjects into a hat and draw them out one by one, or assign each member a number and choose every fifth number to be a participant.Probability sampling=A sampling procedure in which the probability that each element of the population will be included in the sample can be specified; you have a specific number of subjects and you know that they have a 50/50 chance of being chosen, or because of an anomaly, they may only have a 20/100 chance of being chosen for the experiment.*Your teacher is being tricky however, because there are 4 basic types of Probability sampling and simple random sampling is one of them. Also are stratified, systematic and cluster sampling. All four fall under the general title of Probability Sampling (P.S.)!! P.S. is kinda like the category and the 4 types are just different ways to do the sample, each has their own "little differences" in how the data is collected and assigned.
How many different possible combinations of the four different nitrogen bases taken three at a time?
Four of them.
What are four kinds of sampling techniques?
Four sampling techniques are:1) Simple Random SamplingThis is the ideal choice as it is a 'perfect' random method. Using this method, individuals are randomly selected from a list of the population and every single individual has an equal chance of selection.This method is ideal, but if it cannot be adopted, one of the following alternatives may be chosen if any shortfall in accuracy.2) Systematic SamplingSystematic sampling is a frequently used variant of simple random sampling. When performing systematic sampling, every kth element from the list is selected (this is referred to as the sample interval) from a randomly selected starting point. For example, if we have a listed population of 6000 members and wish to draw a sample of 2000, we would select every 30th (6000 divided by 200) person from the list. In practice, we would randomly select a number between 1 and 30 to act as our starting point.The one potential problem with this method of sampling concerns the arrangement of elements in the list.? If the list is arranged in any kind of order e.g. if every 30th house is smaller than the others from which the sample is being recruited, there is a possibility that the sample produced could be seriously biased.3) Stratified SamplingStratified sampling is a variant on simple random and systematic methods and is used when there are a number of distinct subgroups, within each of which it is required that there is full representation. A stratified sample is constructed by classifying the population in sub-populations (or strata), base on some well-known characteristics of the population, such as age, gender or socio-economic status. The selection of elements is then made separately from within each strata, usually by random or systematic sampling methods.Stratified sampling methods also come in two types - proportionate and disproportionate.In proportionate sampling, the strata sample sizes are made proportional to the strata population sizes.For example if the first strata is made up of males, then as there are around 50% of males in the UK population, the male strata will need to represent around 50% of the total sample. In disproportionate methods, the strata are not sampled according to the population sizes, but higher proportions are selected from some groups and not others. This technique is typically used in a number of distinct situations:The costs of collecting data may differ from subgroup to subgroup.We might require more cases in some groups if estimations of populations values are likely to be harder to make i.e. the larger the sample size (up to certain limits), the more accurate any estimations are likely to be.We expect different response rates from different groups of people. Therefore, the less co-operative groups might be 'over-sampled' to compensate.4) Cluster or Multi-stage SamplingCluster sampling is a frequently-used, and usually more practical, random sampling method. It is particularly useful in situations for which no list of the elements within a population is available and therefore cannot be selected directly. As this form of sampling is conducted by randomly selecting subgroups of the population, possibly in several stages, it should produce results equivalent to a simple random sample.The sample is generally done by first sampling at the higher level(s) e.g. randomly sampled countries, then sampling from subsequent levels in turn e.g. within the selected countries sample counties, then within these postcodes, the within these households, until the final stage is reached, at which point the sampling is done in a simple random manner e.g. sampling people within the selected households. The 'levels' in question are defined by subgroups into which it is appropriate to subdivide your population.Cluster samples are generally used if:- No list of the population exists.- Well-defined clusters, which will often be geographic areas exist.- A reasonable estimate of the number of elements in each level of clustering can be made.- Often the total sample size must be fairly large to enable cluster sampling to be used effectively.Non-probability Sampling MethodsNon-probability sampling procedures are much less desirable, as they will almost certainly contain sampling biases. Unfortunately, in some circumstances such methods are unavoidable. In a Market Research context, the most frequently-adopted form of non-probability sampling is known as quota sampling.? In some ways this is similar to cluster sampling in that it requires the definition of key subgroups. The main difference lies in the fact that quotas (i.e. the amount of people to be surveyed) within subgroups are set beforehand (e.g. 25% 16-24 yr olds, 30% 25-34 yr olds, 20% 35-55 yr olds, and 25% 56+ yr olds) usually proportions are set to match known population distributions. Interviewers then select respondents according to these criteria rather than at random. The subjective nature of this selection means that only about a proportion of the population has a chance of being selected in a typical quota sampling strategy.If you are forced into using a non-random method, you must be extremely careful when drawing conclusions. You should always be honest about the sampling technique used and that a non-random approach will probably mean that biases are present within the data. In order to convert the sample to be representative of the true population, you may want to use weighting techniques.The importance of sampling should not be underestimated, as it determines to whom the results of your research will be applicable. It is important, therefore to give full consideration to the sampling strategy to be used and to select the most appropriate. Your most important consideration should be whether you could adopt a simple random sample.? If not, could one of the other random methods be used? Only when you have no choice should a non-random method be used.All to often, researchers succumb to the temptation of generalising their results to a much broader range of people than those from whom the data was originally gathered. This is poor practice and you should always aim to adopt an appropriate sampling technique. The key is not to guess, but take some advice.
How many different 4 letter combinations can you make with 6 different letters?
6P4 = 6!/(6-4)! = 6 * 5 * 4 * 3 = 360 four letter permutations from 6 different letters.6C4 = 6!/[4!∙(6-4)!] = 15 four letter combinationsfrom 6 different letters.
Using four different digits what is the least sum you can get when you add two digit numbers?
2222
What are four different advertising techniques?
There are a great many different advertising techniques. Someone might come up with a commercial, radio ad, posters, or a song for example.
What are the four types of random sampling?
geese cat monkeys cows
What is the answer for a rectangle of 29ft 9ft 15ft 17ft?
More important, what is the question? Four different lengths do not define a rectangle.
What are the main debridement techniques?
The four major debridement techniques are surgical, mechanical, chemical, and autolytic
How many different types of biopsy methods are there?
There are four types of biopsy techniques. Aspiration biopsy, Needle biopsy, Incisional biopsy, Excisional biopsy
Which term is define as a four-line stanza?
Quatrain
How do you define the term quadrilaterals?
A plane figure having four sides and four angles
What are four methods of determining populations size?
what are four methods of determining populations size?
How does one start a new online business?
Although there are different approaches for different types of business, one can define the following four steps. The first step is to find a need that the new business can provide. The second step is to define a financial logic to support the business. The third step is to find a way to attract visitors. Finally, the four step is to determine how much of the business is dependent on the website.
How many triangles are in a 4-sided polygon?
You could draw four different triangles in a 4-sided polygon, but two are enough to define the polygon.
What is the difference between probability sampling and simple random sampling?
Simple random sampling = A process of selecting subjects in such a way that each member of the population has an equal likelihood of being selected; you can throw all your subjects into a hat and draw them out one by one, or assign each member a number and choose every fifth number to be a participant.Probability sampling=A sampling procedure in which the probability that each element of the population will be included in the sample can be specified; you have a specific number of subjects and you know that they have a 50/50 chance of being chosen, or because of an anomaly, they may only have a 20/100 chance of being chosen for the experiment.*Your teacher is being tricky however, because there are 4 basic types of Probability sampling and simple random sampling is one of them. Also are stratified, systematic and cluster sampling. All four fall under the general title of Probability Sampling (P.S.)!! P.S. is kinda like the category and the 4 types are just different ways to do the sample, each has their own "little differences" in how the data is collected and assigned.
How do you define a rectangle?
a rectangle is any quadrilateral with four right angles
