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No: the opposite.

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Q: Is sampling distribution more compact when is is based on smaller samples?
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Is the range in distribution ever smaller than standard deviation in a distribution?

No.


What is the difference between multiphase sampling and multistage sampling?

Oh, dude, like, multiphase sampling is when you have different phases within one stage, while multistage sampling is like a multilevel marketing scheme where you have different stages with different samples. So, like, multiphase is more about breaking down one big stage into smaller phases, and multistage is about moving through different stages to get your final sample. Hope that clears things up for you!


Advantages and disadvantages of systematic sampling?

Advantages 1.It is very simple to use. 2.It also saves time and cost. 3.It checks bias in subsequent selections of samples. 4.Its variances are most often smaller than other alternative sampling technique,when it is suitable to use. Disadvantages 1.There is the possibility of losing vital information from the population. 2.It may not be possible to select the required sample size if the population is too small. 3.It may not be good for periodic data.


The law of large numbers affects sampling procedure how?

Statistical concept that larger the sample population (or the number of observations) used in a test, the more accurate the predictions of the behavior of that sample, and smaller the expected deviation in comparisons of outcomes.


Is the mean and median similar?

The Mean is the average of a given set of values. The Median is the value that has the same number of smaller values than the number of higher values, it is in the middle of them. In a symmetrical distribution the Mean is equal to the Median. In an asymmetrical distribution they have different value.

Related questions

Is compact or sub compact smaller?

Sub compact is smaller than compact.


What is the difference between standard normal distribution table and the t distribution table?

standard normal is for a lot of data, a t distribution is more appropriate for smaller samples, extrapolating to a larger set.


How does the number of repetitions effect the shape of the normal distribution?

When we discuss a sample drawn from a population, the larger the sample, or the large the number of repetitions of the event, the more certain we are of the mean value. So, when the normal distribution is considered the sampling distribution of the mean, then more repetitions lead to smaller values of the variance of the distribution.


What are the disadvantages of random sampling?

used for a smaller population


What is a condencer?

Make smaller, compact.


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.


Is the range in distribution ever smaller than standard deviation in a distribution?

No.


Why do compact cameras use such small sensors?

The answer is in your question. They need smaller sensors to fit in smaller and smaller cameras. The full size DSLR camera has sensor as big as the old 35 mm film. Most compact camera have sensors the size of you fingernail or smaller.


What census taking method do you take on killer whales?

sampling in a large area or tagging in a smaller area


Are cells smaller then chromosomes?

No, chromosomes are compact pieces of DNA that are found within a cell, and are therefore smaller than a cell.


What gets smaller the more you pull on it?

A knot. The tighter you pull on a knot, the smaller and more compact it becomes.


Assume that the percentage of the total time that any given phase take sis equal to the percentage of cells in that phase at any moment Why might this not be true for very small samples of cel?

In very small samples of cells, the random distribution of cells in different phases may not reflect the true distribution seen in a larger population due to statistical variability. Sampling error and the small sample size can lead to deviations from the expected percentage of cells in each phase, which may not accurately represent the overall cell cycle dynamics of a larger population.