If random samples of size n are drawn from a population, then as n becomes larger, the sampling distribution of the mean approaches the normal distribution regardless of the shape of the population distribution. This is known as CENTRAL LIMIT THEOREM. The Central Limit Theorem may apply to any sample size but the ideal number of sample is at least 30 so that the data will be more reliable.
If random samples of size n are drawn from a population, then as n becomes larger, the sampling distribution of the mean approaches the normal distribution regardless of the shape of the population distribution. This is known as CENTRAL LIMIT THEOREM. The Central Limit Theorem may apply to any sample size but the ideal number of sample is at least 30 so that the data will be more reliable.
A First Course in Probability (10th Edition)
10th Edition
ISBN:9780134753119
Author:Sheldon Ross
Publisher:Sheldon Ross
Chapter1: Combinatorial Analysis
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Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...
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![V. SYNTHESIS:
If random samples of size n are drawn from a population, then as n becomes larger, the
sampling distribution of the mean approaches the normal distribution regardless of
the shape of the population distribution. This is known as CENTRAL LIMIT
THEOREM. The Central Limit Theorem may apply to any sample size but the ideal
number of sample is at least 30 so that the data will be more reliable.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F539518d1-e077-4f5e-97ec-89441ae9ca67%2Fa650e6f0-7687-4619-9e8f-0465eabc152d%2Fg9ci2r_processed.jpeg&w=3840&q=75)
Transcribed Image Text:V. SYNTHESIS:
If random samples of size n are drawn from a population, then as n becomes larger, the
sampling distribution of the mean approaches the normal distribution regardless of
the shape of the population distribution. This is known as CENTRAL LIMIT
THEOREM. The Central Limit Theorem may apply to any sample size but the ideal
number of sample is at least 30 so that the data will be more reliable.
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