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What sampling technique will be the best for the large population size?
Wiki User
∙ 10y ago
Clustered sampling.
Clustered sampling.
Clustered sampling.
Clustered sampling.
Wiki User
∙ 10y ago
Wiki User
∙ 10y agoClustered sampling.
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Which rhetorical technique does it best exemplify A. Understatement B. Alliteration C. Connotation?
Apex perallelism
Which type of graph would be best for showing how the population of a country changes each month?
line graph
Why is standard deviation called the best of all measures of dispersion?
standard deviation is the best measure of dispersion because.. a)It measure the absolute dispersion b)It is most frequentlyused as prossesses almost all the the qualities that a good measure of variation have. c)It is beased on all observation. d)It is rigidly defined. e)It is capable of further algebraic treatment. f)It is least affected by the fluctuation of sampling.
What is this number 300000000000000?
Such large numbers are best written in scientific notation. In this case, 3 x 1014.
Which choice gives the best representations of frequencies of categorical data from large data sets?
bar graph
How to reduce sampling error?
The only way to get rid of sampling error is to use the entire population under study. This is usually impossible, so the next best thing is to use large samples and good sampling methods.
What is consecutive sampling?
Consecutive sampling is very similar to convenience sampling except that it seeks to include ALL accessible subjects as part of the sample. This non-probability sampling technique can be considered as the best of all non-probability samples because it includes all subjects that are available that makes the sample a better representation of the entire population.
How can sampling error be reduced?
The best way to reduce sampling error is to use random sampling in the study. This means selecting the population to study through a random process. This will ensure that each member of the population under study has an equal chance of being selected.
College has a student population of 60000 Determine a sample size with confidence level of 95 percent that will show true proportion of population in favor of new system within plus and minus 0.02?
Use snowball sampling!!! The best sampling method there is! Yeah!! WOohOo!!
You are in charge of promoting a new flavor of toothpaste yet to be produced in a toothpaste manufacturing unit which sampling techniques will you use to get the required data from a population?
Sampling is that part of statistical practice concerned with the selection of individual observations intended to yield some knowledge about a population of concern, especially for the purposes of statistical inference. Each observation measures one or more properties (weight, location, etc.) of an observable entity enumerated to distinguish objects or individuals. Survey weights often need to be applied to the data to adjust for the sample design. Results from probability theory and statistical theory are employed to guide practice. In business, sampling is widely used for gathering information about a populationIt is incumbent on the researcher to clearly define the target population. There are no strict rules to follow, and the researcher must rely on logic and judgment. The population is defined in keeping with the objectives of the study.Sometimes, the entire population will be sufficiently small, and the researcher can include the entire population in the study. This type of research is called a census study because data is gathered on every member of the population.Usually, the population is too large for the researcher to attempt to survey all of its members. A small, but carefully chosen sample can be used to represent the population. The sample reflects the characteristics of the population from which it is drawn.Sampling methods are classified as either probability or non-probability. In probability samples, each member of the population has a known non-zero probability of being selected. Probability methods include random sampling, systematic sampling, and stratified sampling. In non-probability sampling, members are selected from the population in some non-random manner. These include convenience sampling, judgment sampling, quota sampling, and snowball sampling. The advantage of probability sampling is that sampling error can be calculated. Sampling error is the degree to which a sample might differ from the population. When inferring to the population, results are reported plus or minus the sampling error. In non probability sampling, the degree to which the sample differs from the population remains unknown.· Random samplingis the purest form of probability sampling. Each member of the population has an equal and known chance of being selected. When there are very large populations, it is often difficult or impossible to identify every member of the population, so the pool of available subjects becomes biased.· Systematic sampling is often used instead of random sampling. It is also called an Nth name selection technique. After the required sample size has been calculated, every Nth record is selected from a list of population members. As long as the list does not contain any hidden order, this sampling method is as good as the random sampling method. Its only advantage over the random sampling technique is simplicity. Systematic sampling is frequently used to select a specified number of records from a computer file.· Stratified sampling is commonly used probability method that is superior to random sampling because it reduces sampling error. A stratum is a subset of the population that share at least one common characteristic. Examples of stratums might be males and females, or managers and non-managers. The researcher first identifies the relevant stratums and their actual representation in the population. Random sampling is then used to select a sufficient number of subjects from each stratum. "Sufficient" refers to a sample size large enough for us to be reasonably confident that the stratum represents the population. Stratified sampling is often used when one or more of the stratums in the population have a low incidence relative to the other stratums.· Convenience sampling is used in exploratory research where the researcher is interested in getting an inexpensive approximation of the truth. As the name implies, the sample is selected because they are convenient. This non-probability method is often used during preliminary research efforts to get a gross estimate of the results, without incurring the cost or time required to select a random sample.· Judgment sampling is a common non-probability method. The researcher selects the sample based on judgment. This is usually an extension of convenience sampling. For example, a researcher may decide to draw the entire sample from one "representative" city, even though the population includes all cities. When using this method, the researcher must be confident that the chosen sample is truly representative of the entire population.· Quota samplingis the non-probability equivalent of stratified sampling. Like stratified sampling, the researcher first identifies the stratums and their proportions as they are represented in the population. Then convenience or judgment sampling is used to select the required number of subjects from each stratum. This differs from stratified sampling, where the stratums are filled by random sampling.· Snowball sampling is a special non-probability method used when the desired sample characteristic is rare. It may be extremely difficult or cost prohibitive to locate respondents in these situations. Snowball sampling relies on referrals from initial subjects to generate additional subjects. While this technique can dramatically lower search costs, it comes at the expense of introducing bias because the technique itself reduces the likelihood that the sample will represent a good cross section from the population.If I were an officer to promote a new flavour of toothpaste yet to be produced, I would use RANDOM SAMPLING METHODØ Random sampling:Random sampling- all members of the population have an equal chance of being selected as part of the sample. You might think this means just standing in the street and asking passers-by to answer your questions. However, there would be many members of the population who would not be in the street at the time you are there; therefore, they do not stand any chance of being part of your sample. To pick a random sample, it is necessary to take all the names on the electoral register (A list of all the people who live in a particular area) and pick out, for example, every fiftieth name. This particular person needs to be interviewed to make the sample truly random. Random sampling is very expensive and time consuming, but gives a true sample of the population.Types of Random sample:A simple random sample is selected so that all samples of the same size have an equal chance of being selected from the population.A self-weighting sample, also known as an EPSEM (Equal Probability of Selection Method) sample, is one in which every individual, or object, in the population of interest has an equal opportunity of being selected for the sample. Simple random samples are self-weighting.Stratified sampling involves selecting independent samples from a number of subpopulations, group or strata within the population. Great gains in efficiency are sometimes possible from judicious stratification.Cluster sampling involves selecting the sample units in groups. For example, a sample of telephone calls may be collected by first taking a collection of telephone lines and collecting all the calls on the sampled lines. The analysis of cluster samples must take into account the intra-cluster correlation which reflects the fact that units in the same cluster are likely to be more similar than two units picked at randomØ Pros and Cons:1. There are lot of bias in Random sampling2. It is feasible and simple as the sampling is done on a random basis.3. Can make sample units in groups.4. Very expensive and time consuming, but gives a true result of the population5. While in toothpaste case, the users can given a sample piece of toothpaste randomly to get the feedback or their opinion from the chosen populationConclusion: Though the Random sampling has couple of de-merits it will help to figure out the result from the chosen population. While all other also may provide the result which may not be best comparing to the sampling method which I have chosen (Random Sampling)
When would random sampling not be the best approach to sample selection?
When would random sampling not be the best approach to sample selection
The best most reliable sampling technique is the one that has the smallest chance of unknowingly producing biased results in a study?
Convenience sample Systematic sample Simple random sample (SRS) Census
Is the best description of a stratified random sample?
Stratified random sampling is a form of probability sampling that provides a methodology for dividing a population into smaller subgroups as a means of ensuring greater accuracy of your high-level survey results. The smaller subgroups are called strata. Stratified random sampling is also called proportional or quota random sampling.
Which sampling method would be best for a large multi-site corporation employee survey?
When carrying out a multi-site corporation employee survey, stratified sampling will give good results. Subsets of the employees, called strata, are used to save time and resources.
When is the best time to collect soil sample?
Samples for what? If you are sampling for the basic test that most extension offices perform, it doesn't matter.
When should Chorionic villus sampling be done?
Chorionic villus sampling is best performed between 10 and 12 weeks of pregnancy
What Constitutional Convention the Virginia Plan would have granted more power to?
granted power to the states with a large population and Carmelo Anthony is the best nba player joe flacco is the best nfl player
