Assertion: sample's mean | /r/HasProperty | distributed
Facets:
value: normally
type: DEGREE
value: based on the central limit theorem
type: OTHER
value: fairly
type: DEGREE
value: approximately
type: DEGREE
Source sentences:
text: This means, the distribution of sample means for a large sample size is normally distributed irrespective of the shape of the universe, but provided the population standard deviation (σ) is finite.
text: Based on the Central Limit Theorem, if you draw samples from a population that is greater than or equal to 30, then the sample mean is a normally distributed random variable.
text: How do we know that the mean is normally distributed?
text: As a general rule, sample sizes equal to or greater than 30 are deemed sufficient for the CLT to hold, meaning that the distribution of the sample means is fairly normally distributed.
text: For samples that are sufficiently large it turns out that the mean of the sample is normally distributed (the Central Limit Theorem), and so the techniques described for the normal distribution can be used.
text: We can count on the sampling distribution of the mean being approximately normally distributed , no matter what the original population distribution looks like as long as the sample size is relatively large.
text: When the original variable is normally distributed, the distribution of the sample means will be normally distributed
text: According to Central Limit Theorem for large samples the means of sampling distribution are normally distributed.