1. The variable x is skewed, based on the sample sizes given does the central limit theorem tell us that the sample means is normally distributed?
(A) A sample size of 40?
(B) A Sample Size of 15?
Solution:
The population is not normally distributed. It is skewed. In this case the sampling distribution of sample means is normally distributed if and only if sample size n 30.
A) Here n = 40 > 30
So ,
YES , the central limit theorem tells us that the
sample means is normally distributed.
B) Here n = 15 < 30
So ,
NO , the central limit theorem does not tells us that the sample means is normally distributed.
1. The variable x is skewed, based on the sample sizes given does the central limit...
According to the central limit theorem, Multiple Choice O sample size is important when the population is not normally distributed Increasing the sample size decreases the dispersion of the sampling distribution the sampling distribution of the sample means is uniform O sample size is important when the population is not normally distributed Increasing the sample size decreases the dispersion of the sampling distribution the sampling distribution of the sample means is uniform the sampling distribution of the sample means will...
A simple random sample of size n 43 is obtained from a population that is skewed left with = 54 and 06. 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. The central limit theorem states that only if the...
Choose all that are true about the central limit theorem a. sample size is important when the population is not normally distributed b. the sampling distribution of the sample means will be skewed positively or negatively c. the sampling distribution of the sample means is approximately normally distributed d. the population mean and the mean of all sample means are equal PLEASE DO NOT ANSWER IF YOU DO NOT KNOW. I need to learn from these questions that I do...
ILUL. In which case can I NOT use the Central Limit Theorem for means? The sample size n is less than 30 and the data is not normally distributed. The sample size n is greater than 30 and the data is not normally distributed. The sample size n is greater than 30 and the data is normally distributed. The sample size n is less than 30 and the data is normally distributed. Points possible: 1 Unlimited attempts. Submit
Which of the following conditions implies that the Central Limit Theorem can be applied? A. The population is approximately normally distributed B. The sample is approximately normally distributed C. σ is not known D. μ is not known E. μ is known Which of the following conditions implies that the Central Limit Theorem can be applied? A. The sample is approximately normally distributed B. The sample size is at least 30 C. μ is not known D. σ is not...
17. According to the Central Limit Theorem, a distribution of sample means based on a sample of n= 7 will approximate normality even if the data in the parent population are not normal. 18. When performing hypothesis tests or computing confidence intervals based on large samples, it is necessary to assume that the data in the parent population(s) are distributed normally. 19. To estimate u within two units with 95% confidence and o= 10 requires n be at least 100.
The central limit theorem states that if the original population is normally distributed and the sample size is large (≥30), then the distribution of x ̅ is also approximately normal. True OR False
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...
by central limit theorem 12. Suppose that X1, X2, ..., X 40 denote a random sample of measurements on the proportion of impurities in iron ore samples. Let each variable X have a probability density function given by 132 0<x<1 o elsewhere The ore is to be rejected by the potential buyer if sample of size 40 X, exceeds 2.8. Estimate P ., X. > 2.8) for the
Explain the importance of the Central Limit Theorem. How does this relate to a sample size of 20 versus a sample size of 40? Explain your answer. Use examples.