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A histogram representing a sample taken from a population that is uniform?

For a large enough sample, it will resemble a rectangle whose base will be the range of the variable and the height will be the reciprocal of the number (or width) of the base.


Does the central limit theorem allows the use of the normal distribution to analyze the sample mean if the sample sizes are large enough?

Yes. Roughly, very large samples are very likely to have subsets data points having very similar means and distributions. Large numbers of such subsets will tend to be normal distributed (Why?) and will tend to make the total sample be normally distributed.


Why use sample instead of population?

When performing an experiment or gathering data for statistics, it would be very difficult to gather information for every member of the group's population. Instead, one can gather information from a sample large enough to be representative of the population.


What is A sample of a population should be small enough to do?

A sample of a population should be small enough to allow for efficient data collection and analysis while still being representative of the population. This ensures that the results can be generalized without being overly burdensome in terms of time and resources. Additionally, a smaller sample can facilitate quicker decision-making and reduce costs, while still capturing the essential characteristics of the larger group. However, it must be large enough to maintain statistical validity and reliability.


Why does a statistical sample have to be large?

The larger the sample of data collected leads to a more accurate conclusion.

Related Questions

Is Darmstadtium a solid?

No large enough sample has been prepared to know what the phase is.


How large should the sample be to be large enough?

Span the full spectrum of a population's genetic variation. <apex> Reflects the genetic variation of a population...


A histogram representing a sample taken from a population that is uniform?

For a large enough sample, it will resemble a rectangle whose base will be the range of the variable and the height will be the reciprocal of the number (or width) of the base.


Why is a large sample better than a small sample?

A large sample will reduce the effects of random variations.


Does the central limit theorem allows the use of the normal distribution to analyze the sample mean if the sample sizes are large enough?

Yes. Roughly, very large samples are very likely to have subsets data points having very similar means and distributions. Large numbers of such subsets will tend to be normal distributed (Why?) and will tend to make the total sample be normally distributed.


A sample of a population should be large enough to?

span the full spectrum of a population's genetic variation.-apexI got you guysssss.feel free to hmu on snap king.youssof ( need knew friends ;--;)


How can you compare means of two samples when the samples are chi square distributed?

According to the Central Limit Theorem if the sample size is large enough then the means will tend towards a normal distribution regardless of the distribution of the actual sample.


Disadvantages of a large sample size confidence Interval in statistices?

A disadvantage to a large sample size can skew the numbers. It is better to have sample sizes that are appropriate based on the data.


A sample average can be used to estimate a population average precision if the sample is?

large


Why use sample instead of population?

When performing an experiment or gathering data for statistics, it would be very difficult to gather information for every member of the group's population. Instead, one can gather information from a sample large enough to be representative of the population.


What properties should a sample have?

A sample should be representative of the population it is drawn from, have enough data points to provide reliable conclusions, and be selected randomly or systematically to minimize bias. Additionally, samples should be sufficiently large to ensure statistical significance.


What two features must a sample have to accurately represent a population?

A sample must be representative, meaning that it reflects the characteristics of the population it is drawn from. It must also be large enough to minimize sampling error and increase the likelihood of capturing the population's diversity.