In order for the Central Limit Theorem to apply, what distribution must the underlying data have? (assuming ? is large enough) A. Normal distribution B. Bernoulli distribution C. Binomial distribution D. Uniform distribution E. Any distribution
according to clt
if x have a distribution with mean mu and standard deviation sigma then (xbar-mu)/ sigma follows standard normal distribution.(if n is large enough)
So from CLT defination we get that distribution can be any.
E. any distribution.
In order for the Central Limit Theorem to apply, what distribution must the underlying data have?...
What is the main concept behind the central limit theorem? The Poisson and the Binomial distributions are the same at large sample sizes As sample size increases, continuous data will assume the shape of the normal distribution As sample size increases, continuous data will assume the shape of the binomial distribution The Normal distribution at large sample sizes approximates the Lognormal distribution
1. Explain, in your own words, what the Central Limit Theorem says about sample means. In particular, discuss what the Central Limit Theorem says about the distribution of the sample mean, the mean of the sample mcan, and the standard deviation of the sample mean, as well as what effect (if any) the distribution of the underlying sample data has on the distribution of the sample mean. (You should consult my slides from class. Supplement with internet resources if you...
According to the central limit theorem, for any population, the sampling distribution of the sample mean x bar is approximately normal if A. sample size is n >=30 B. population mean is known C. population standard deviation is known D. underlying sample is normal.
According to the central limit theorem, in order to assume a normal distribution for our sample mean if σ is unknown, we must have a sample size greater than ____.
The Central Limit Theorem (CLT) implies that: A: the mean follows the same distribution as the population B: repeated samples must be taken to obtain normality C: the population will be approximately normal if n ≥ 30 D: the distribution of the sample mean will be normal with large n
The Central Limit Theorem states that the sampling distribution will be normal as long as the subgroup size is large enough. Explain what role the subgroup size has on the Variability of the means
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QUESTION 7 According to the Central Limit Theorem, the distribution of which statistic can be approximately normal for any population distribution? What condition should the sample satisfy? 6. The Central Limit Theorem approximates the sample mean . It is applicable when the sample size n is sufficiently large. b. The Central Limit Theorem approximates the sample size n. It is applicable when the sample size is not large. The Central Limit Theorem approximates the population mean...
The Central Limit Theorem basically states that the sampling distribution will be normal as long as the subgroup size is large enough. Explain what role the subgroup size has on the: a. normality of the means. b. variability of the means
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QUESTION 3 According to the central limit theorem, which of the following distributions tend towards a normal distribution? (choose all that apply) a. Binomial distribution as number of events (number of total coin flips) increase U b.Sum of m independent samples from a normal distribution as m increases UC. Mean of n independent samples from a chi-squared distribution as n increases d. Sampling distribution of the mean from ANY population distribution as the sample size increases
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...