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Providing of course that a sample is representative of the population from which it is drawn, the bigger it is the more likely it will be to lead to a valid conclusion. Therefore, the best sample size when there are no restrictions, as in this case, would be one of 1000.
It is quite likely that the sample is not representative of the population and so while statistical conclusion may be valid for the sample, they may not apply to the population.
i might be mistaken but i think 10
It is strangely worded like that, but the answer is yes.
Portion of the entire population used to estimate what is likely happening within a population.
Providing of course that a sample is representative of the population from which it is drawn, the bigger it is the more likely it will be to lead to a valid conclusion. Therefore, the best sample size when there are no restrictions, as in this case, would be one of 1000.
It is quite likely that the sample is not representative of the population and so while statistical conclusion may be valid for the sample, they may not apply to the population.
i might be mistaken but i think 10
The best estimator of the population mean is the sample mean. It is unbiased and efficient, making it a reliable estimator when looking to estimate the population mean from a sample.
It is strangely worded like that, but the answer is yes.
Assuming that the population was carefully defined, the sample population was carefully and correctly chosen, and that there were significant results, then the implication is that the results of the study, within the confidence limits indicated, hold true for the population at large.
Portion of the entire population used to estimate what is likely happening within a population.
The variance decreases with a larger sample so that the sample mean is likely to be closer to the population mean.
The use of a small number of people to represent a greater population is called sampling. The sample can be randomly chosen so that it is a reliable reflection of most of the population.
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The most important step to ensure accuracy in a sample is random selection. By randomly choosing samples from the population, you minimize bias and increase the likelihood that your sample is representative of the entire population. This helps to draw reliable conclusions and make valid inferences based on the sample data.
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 ;--;)