0
Yes, if under simple random sampling there are likely to be too few representatives from a certain subset of the population in which you might have an interest.
Wiki User
∙ 14y ago
Add your answer:
Earn +20 pts
Is questionnaire probability sampling technique?
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.
Is there any Advantages of simple random sampling?
Cheap, simple, easily applied to a small population ensures bias is not introduced
Different types of random and non random sampling?
stratified sampling, in which the population is divided into classes, and random samples are taken from each class;cluster sampling, in which a unit of the sample is a group such as a household; andsystematic sampling, which refers to samples chosen by any system other than random selection.
Why should your sampling be random?
Random sampling prevents any emergent patterns inherent in a non-random selection process. Second, random samples of the population provide the widest representation of the population as a whole (given that the sample is large enough). This is why there is emphasis and the quantity of the study group-- the larger the population being analyzed the more accurate a representation it will be during the course of the study.
What happens When a random sampling frame has a systematic pattern in the listing of sampling units rather than a random pattern?
You get a non-random sample and any analysis based on the assumption of randomly distributed variables is no longer valid. In particular, your estimates of any variables are likely to be biased and your error estimates (standard errors or sample variances) will be incorrect. Any inferences based on statistical tests will be less reliable and may be wrong.
Is questionnaire probability sampling technique?
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.
Are there any advantages of stratified random sampling?
Yes because it gives a representation of all the data! <3
Is there any Advantages of simple random sampling?
Cheap, simple, easily applied to a small population ensures bias is not introduced
Different types of random and non random sampling?
stratified sampling, in which the population is divided into classes, and random samples are taken from each class;cluster sampling, in which a unit of the sample is a group such as a household; andsystematic sampling, which refers to samples chosen by any system other than random selection.
What statistical tests can I use on data collected from quota samples?
You can use statistical tests appropriate for categorical data, such as chi-square tests or Fisher's exact test for associations between variables. For continuous data, you can use t-tests or non-parametric tests like Mann-Whitney U test or Kruskal-Wallis test. It's important to consider the limitations of quota sampling in interpreting the results.
What is random sampleng?
Random sampling can be defined as the selection of a random sample; each element of the population had an equal chance of been selected. Random sampling is used in psychology, statistics, math, sociology, movement and research.
Are probability and random sampling anonymous?
Probability is a branch of mathematics and so is not linked with any individual and so is anonymous. Random sampling may or may not include information that will allow the contributor to be identified. So it may or may not be anonymous.
Example of multistage sampling?
the combinitoin of any random samples is called multistage samplinag. it is the expensive form of cluster samling. when each elements in cluster are expensive then we use multistage sampling.
Why should your sampling be random?
Random sampling prevents any emergent patterns inherent in a non-random selection process. Second, random samples of the population provide the widest representation of the population as a whole (given that the sample is large enough). This is why there is emphasis and the quantity of the study group-- the larger the population being analyzed the more accurate a representation it will be during the course of the study.
What are the advantages and disadvantages of random sampling?
The main advantage is that the sample is representative of the population and the mean of the sample is an unbiased estimate of the population mean. Also, characteristics of other statistics based on the sample are well understood. However, sometimes it may not be possible to gather valid information from a sampling unit and then the sample is no longer random. This can be either because the sampling unit cannot be located or has been compromised by external factors. This can be particularly serious if the "missing" units share a common characteristic. Also, simple random samples may not include any units representing characteristics that are rare in the population - but important in the context of the experiment.
What happens When a random sampling frame has a systematic pattern in the listing of sampling units rather than a random pattern?
You get a non-random sample and any analysis based on the assumption of randomly distributed variables is no longer valid. In particular, your estimates of any variables are likely to be biased and your error estimates (standard errors or sample variances) will be incorrect. Any inferences based on statistical tests will be less reliable and may be wrong.
What is the random sampling method?
Random sampling is a method of selecting a sample where each member of the population has the same probability of being included in the sample. An equivalent statement is that each subset of the population, of the given size, has the same probability of being selected as any other subset of that size.
