the central limit theorem states that the sampling distribution of the sample mean is approximately normal whenever the population from which we are sampling is normally distributed
TRUE
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Sample size , n = 50
Probability of an event of interest, p =0.14
and probability is given by
P(X=x) = C(n,x)*px*(1-p)(n-x) |
P(X≥5) = 1 - [ P(X=0) + P(X=1) + P(X=2) + P(X=3) + P(X=4) ] = 0.8472(answer)
probability that the sample will comtain at least 5 defective items = 0.8472
True or False: the central limit theorem states that the sampling distribution of the sample mean...
The Central Limit Theorem tells us that the sampling distribution of the sample mean can be approximated with a normal distribution for “large”n as n gets bigger, the sample data becomes more like the normal distribution if the data comes from an (approximately) normally distributed population, then the sample mean will also be (approximately) normally distributed the minimum variance unbiased estimator is the "best" estimator for a parameter
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
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...
The central limit theorem states that if a random and representative sample from a population contains more than 15 observations the sampling distribution of the sample mean will be approximately normal
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
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...
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
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.
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.