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The Central limit theorem is important in statistics becouse for a large n, it says the sampling distribution of the sample mean is approximately Normal, regardless of the population.
The Central tumit here is important in too because for any sia wample, it says the...
The Central Limit Theorem is important in statistics because _. A for a large n, it says the population is approximately normal B for any population, it says the sampling distribution of the sample mean is approximately normal, regardless of the sample size C for a large n, it says the sampling distribution of the sample mean is approximately normal, regardless of the population D for any size sample, it says the sampling distribution of the sample mean is approximately...
a
simple random sample of size n=72 is obtained from a population
with u=82 and o=3. does the population need to be normallt
distibuted for the sampling distribution of x to be approximately
normaly distibuted? why? what is the sampling distribution of
x?
A simple random sample of stren72 is obtained from a population with 12 and a = 3. Does the population need to be normally distributed for the sampling distribution of to be approximately omally distributed? Why? What...
If I has a normal distribution, then 7 always has a normal distribution. True False Under what condition does the sample mean ī not have a normal distribution? Population is not normal but the sample size n > 30. Population is not normal and sample size n <30. Population is normal. The Central Limit Theorem for a sample mean (@) is very important in Statistics because it states that for large sample sizes, the population distribution is approximately normal. for...
The central limit theorem says that when a simple random sample of size n is drawn from any population with mean μ and standard deviation σ, then when n is sufficiently large the distribution of the sample mean is approximately Normal. the standard deviation of the sample mean is σ2nσ2n. the distribution of the sample mean is exactly Normal. the distribution of the population is approximately Normal.
A simple random sample of size n = 80 is obtained from a population with u = 55 and 6 = 3. Does the population need to be normally distributed for the sampling distribution of X to be approximately normally distributed? Why? What is the sampling distribution of ? Does the population need to be normally distributed for the sampling distribution of x to be approximately normally distributed? Why? O A. No because the Central Limit Theorem states that regardless...
A simple random sample of size n=74 is obtained from a population with 82 and 8-6 Does the population need to be normally distributed for the sampling distribution of to be approximately normally distributed? Why? What is the sampling distribution of i? Does the population need to be normally distributed for the sampling distribution of to be approximately normally dibuted? Why? O A. No because the Central Limit Theorem states that only if the shape of the underlying population is...
A simple random sample of size n=74 is obtained from a population with u=67 and 5 = 6. Does the population need to be normally distributed for the sampling distribution of x to be approximately normally distributed? Why? What is the sampling distribution of x? Does the population need to be normally distributed for the sampling distribution of x to be approximately normally distributed? Why? A. Yes because the Central Limit Theorem states that the sampling variability of nonnormal populations...
Which of the following statements concerning sampling is false? (1) The Central Limit Theorem is very important for statistical inference. (2) The standard error of an estimator is the standard deviation of a statistic. (3) Regardless of the sample size n, if the population distribution is normal then the sampling distribution of ī will be exactly normal. (4) If the sampled population is uniform then the sampling distribution of ī is also approximately uniform.
Which of the following statements concerning sampling is false? (1) The Central Limit Theorem is very important for statistical inference. (2) The standard error of an estimator is the standard deviation of a statistic. (3) Regardless of the sample size n, if the population distribution is normal then the sampling distribution of ī will be exactly normal. (4) If the sampled population is uniform then the sampling distribution of ī is also approximately uniform.
The Central Limit Theorem says A) When n<30 , the sampling distribution of x¯¯¯ will be approximately a normal distribution. B) When n<30 , the original population will be approximately a normal distribution. C) When n>30 , the original population will be approximately a normal distribution. D) When n>30 , the sampling distribution of x¯¯¯ will be approximately a normal distribution.