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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 small sample size?
One is a small sample size, but that's just my answer, you might want to ask more people.
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 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.
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.
Why would having a larger sample size be a better idea than having a samll sample size when doing an experiment?
less bias and error occur when sample size is larger
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.
What is small sample size?
One is a small sample size, but that's just my answer, you might want to ask more people.
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.
What is rats disadvantages?
Poor eyesight, small size, dependent on man
Which of the following samples will produce the largest value for the estimated standard error?
A small sample size and a large sample variance.
Which is more effective in minimizing instrument error in an experiment?
having a large sample size
