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.
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.
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.
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.
The larger the sample of data collected leads to a more accurate conclusion.
No large enough sample has been prepared to know what the phase is.
Span the full spectrum of a population's genetic variation. <apex> Reflects the genetic variation of a population...
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.
A large sample will reduce the effects of random variations.
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.
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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.
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.
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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.
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.
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.