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In Probability

idon't now, but ask me about American idol. Lolz! the total out come from an experimant is called sample space for example: when tossing a die the out comes are 1, 2 , 3, 4 …,5 & 6 so we can say that the sample space of die is S.S={1, 2, 3, 4, 5, 6} (MORE)

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In Probability

I believe you meant to ask: What distinguishes a random sample from a non random sample? A random sample means the selection or sampling from the population is by c…hance. Looking at the data, one might not be able to tell if the sample is random or selective. Consider a marketing survey which is included everytime you buy an item online. Random or non-random? It is a survey of recent customers, and probably a pretty good one. But it is not a random selection of all customers who have made purchases with clients. (MORE)

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In Probability

In probability sampling,every item in the population has a known chance of being selected as a member.In non-probability sampling, the probability that any item in the populat…ion will be selected for a sample cannot be determined. (MORE)

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In Statistics

A questionnaire has little to do with sampling technique. Sampling technique is to do with who gets the questionnaire and that can be any sampling technique: the questionnaire… can be sent to everyone (census), to a random sample, stratified random samples, to random samples in clusters, by quota or convenience. Or a pile of questionnaires can be left for respondents to pick up - self-selection. (MORE)

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In Statistics

The key feature is that each sample of the given size has the same probability of being selected as the sample. Equivalently, each unit in the population has the same probab…ility of being included in the sample. (MORE)

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In Statistics

In some situations stratified random sampling may be more appropriate. You may have a population which can be divided up into a number of subsets (strata) such that the differ…ence between units in different strata is much greater than the difference between units within each stratum. A probability sample may not have enough units from some of the smaller strata. A stratified random sample will ensure that each stratum is represented proportionally. In other situations, cluster sampling may be more appropriate. Suppose you wish to visit a sample 1% of all schools in the country. If you were to choose the schools by probability sampling they would be all over the country and you would require a huge amount of time and money to visit them all. What you could do, instead, is to divide up the country into 1000 regions. Select 10 of these regions (1%) and then visit every school in the selected regions. Far less running around! (MORE)

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In Education

Probability is used to extrapolate the likelihood of a future event, so if you think about it, it's used all the time by everyone everyday

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In Statistics

In a probability sample, each unit has the same probability of being included in the sample. Equivalently, given a sample size, each sample of that size from the population ha…s the same probability of being selected. This is not true for non-probability sampling. (MORE)

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In Probability

In the context of a sample of size n out of a population of N , any sample of size n has the same probability of being selected. This is equivalent to the statement that …any member of the population has the same probability of being included in the sample. (MORE)

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In Probability

There are many methods: stratified random sampling and cluster sampling are two examples. Suppose you have a school with 1000 pupil: 400 in the Junior school and 600 in the S…enior school. You may wish to keep the sampling proportions in the two parts of the school the same. So if you wanted a sample of 5% = 50 pupils, you would take a probability or random sample of 5% = 20 from the Juniors and 5% = 30 from the Seniors. For the second example, imagine you want to sample 5% of all schools in the country. This could result in you spending lots of time and money travelling from place to place. Instead, you divide up the country into 100 regions - each containing the same number of schools. You then take a probability sample of 5% of these regions. In each of the regions you visit every school. (MORE)