Sample Standard Deviation Dilema??????

Question

When is it best to use sample standard deviation?

a.) When you have a small sample size.

b.) When you have a large sample size.

c.) When the range of your data set is small.

d.) When the first quartile is small.

Please EXPLAIN your answer.

Answer 1

B...

You base much of your statistics-- Not just Standard Deviation-- on a sample when the population is large. You do this because you simply do not have the resources to sample the WHOLE population.

For example: If you wanted to know how much grass was on a golf course you would CRAZY to try and count every blade of grass. You take a sample (count all the grass in a square foot--then multiply by how many square feet a golf course was) so that your job is simplified.

RULE OF THUMB:

The larger the sample size, the more representative it is of the entire population.

Answer 2

in case you calculate the time-honored deviation of a pattern utilising the formula with divisor n, that it given the emblem s. that is shown that it somewhat isn't the terrific obtainable estimate of the time-honored deviation of the inhabitants from which the pattern got here. the terrific estimate is chanced on via utilising n - a million because of the fact the divisor in the formula and this has the emblem sigma.

Answer 3

Stu's 'rule of thumb' is really the 'Central Limit Theorem'.