Respuesta :
Answer:
Sample size
Step-by-step explanation:
Central Limit Theorem states that population with mean and standard deviation and if the sample size is large then the distribution of sample mean will be will be normally distributed. The central limit theorem holds assumptions that the factors to be considered when assessing central limit theorem is sample size.
The CLT is the factor(s) to be considered when assessing if the central theorem holds are sample.
It is given that the objective that central limit theorem assumptions. the factor(s) to be considered when assessing if the central theorem holds.
It is required to describe the above theorem.
What is the central limit theorem?
It is defined as the in statistics the assumption holds that the sample means distribution of arbitrary variables follows a normal distribution or close to normal distribution if the sample size is big.
We have an objective:
The CLT is the factor to be considered when assessing if the CLT holds a large sample size.
If we draw the random sample data and its measures, the Central limit theorem explains the distribution will explain the normal bell curve, the mean of the parameters and the distribution will be the same.
Thus, the CLT is the factor(s) to be considered when assessing if the central theorem holds are sample.
Learn more about the Central limit theorem here:
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