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Where the standard deviation is not applicable?
When the sample size is small
Will a large sample size and a small sample variance produce the largest value for the estimated standard error?
no
Why is having a larger sample size be a better idea than having a small sample size when doing a experiment?
1. Better chance of uniform sample. 2. Material for confirmations if needed.
What is absolute sample size?
It is the number of elements in the sample. By contrast, the relative sample size is the absolute sample size divided by the population size.
How To get valid results small samples are sufficient?
I will assume the sample is random. In general, the larger the sample, the smaller the percentage error will be (the difference between percentages in the sample, and the percentages in the universe from whence the sample is taken). The percentage error tends to go down as the square root of the size of the sample.
How might choosing a small sample size affect a scientific investigation?
Statistically the results will not be scientifically valid if the sample size is too small.
What property like volume depends of the size of the sample?
The property that depends on the size of the sample is extensive. Extensive properties, such as mass and energy, scale with the size of the sample. This means that as the sample size increases, the value of the property also increases proportionally.
Where the standard deviation is not applicable?
When the sample size is small
Will a large sample size and a small sample variance produce the largest value for the estimated standard error?
no
What does the Central Limit Theorem say about the traditional sample size that separates a large sample size from a small sample size?
The Central Limit Theorem states that the sampling distribution of the sample means approaches a normal distribution as the sample size gets larger — no matter what the shape of the population distribution. This fact holds especially true for sample sizes over 30.
Why is having a larger sample size be a better idea than having a small sample size when doing a experiment?
1. Better chance of uniform sample. 2. Material for confirmations if needed.
Which of the following samples will produce the largest value for the estimated standard error?
A small sample size and a large sample variance.
What is absolute sample size?
It is the number of elements in the sample. By contrast, the relative sample size is the absolute sample size divided by the population size.
Is N the sample or population mean?
N is neither the sample or population mean. The letter N represents the population size while the small case letter n represents sample size. The symbol of sample mean is x̄ ,while the symbol for population mean is µ.
How To get valid results small samples are sufficient?
I will assume the sample is random. In general, the larger the sample, the smaller the percentage error will be (the difference between percentages in the sample, and the percentages in the universe from whence the sample is taken). The percentage error tends to go down as the square root of the size of the sample.
What is the difference between sample and sample size?
a sample is a sample sized piece given... a sample size is the amount given in one sample
What does it means if the standard deviation is large?
that you have a large variance in the population and/or your sample size is too small
