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Context of this question is not clear because it is NOT a full question. However
when attempting to estimate an parameter such as µ using sample data when
the population standard deviation σ is unknown, we have to estimate the standard
deviation of the population using a stastitic called s where
_
Σ(x-x)²
s = ▬▬▬▬
n -1
_
and estimator for µ , in particular x
........................................._
has a standard deviation of s(x)= s/√n
and the statistic
_
x - hypothesized µ
T = ▬▬▬▬▬▬▬▬▬▬
s
has a student's T distribution with n-1 degrees of freedom
If n> 30 , then by the Central Limit Theorem, the T distribution
approaches the shape and form of the normal(gaussian) probability
distribution and the Z table may be used to find needed critical statistical
values for hypothesis tests , p-values, and interval estimates.
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What is the symbol for population standard deviation?
Sigma
Is standard deviation same as standard error?
From what ive gathered standard error is how relative to the population some data is, such as how relative an answer is to men or to women. The lower the standard error the more meaningful to the population the data is. Standard deviation is how different sets of data vary between each other, sort of like the mean. * * * * * Not true! Standard deviation is a property of the whole population or distribution. Standard error applies to a sample taken from the population and is an estimate for the standard deviation.
You take an SRS of size n from a population that has mean 80 and standard deviation 20 How big should n be so that the sampling distribution has standard deviation 1?
400
If quartile deviation is 24. find mean deviation and standard deviation?
Information is not sufficient to find mean deviation and standard deviation.
What percent of a normal population is within 2 standard deviations of the mean?
In a normal distribution, approximately 95% of the population falls within 2 standard deviations of the mean. This is known as the 95% rule or the empirical rule. The empirical rule states that within one standard deviation of the mean, about 68% of the population falls, and within two standard deviations, about 95% of the population falls.
