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When the population standard deviation is not known the sampling distribution is a?
If the samples are drawn frm a normal population, when the population standard deviation is unknown and estimated by the sample standard deviation, the sampling distribution of the sample means follow a t-distribution.
Is the standard deviation of the sampling distribution of the sample mean is o?
NO
As the sample size increases the standard deviation of the sampling distribution increases?
No.
What is Confidence Intervals of Standard Error?
The standard deviation associated with a statistic and its sampling distribution.
Statistics HELP Electrical problems affect about 14 percent of new cars an automobile mechanic conducts diagnostic tests on 128 new cars. Describe the sampling distribution for the sample proportion?
Distribution would be centered at .14*128=17.92The standard deviation of the distribution would be root(n(p(p-1)))=root(128*.14*.86)=3.92571013Normal, unimodal
When the population standard deviation is known the sampling distribution is a?
normal distribution
When the population standard deviation is not known the sampling distribution is a?
If the samples are drawn frm a normal population, when the population standard deviation is unknown and estimated by the sample standard deviation, the sampling distribution of the sample means follow a t-distribution.
When the population standard deviation is known the sampling distribution is known as what?
normal distribution
Is the standard deviation of the sampling distribution of the sample mean is o?
NO
As the sample size increases the standard deviation of the sampling distribution increases?
No.
How do you calculate the mean of the sampling distribution of the sample proportion?
i dont no the answer
What is the sampling distribution when the standard deviation is known?
When the standard deviation of a population is known, the sampling distribution of the sample mean will be normally distributed, regardless of the shape of the population distribution, due to the Central Limit Theorem. The mean of this sampling distribution will be equal to the population mean, while the standard deviation (known as the standard error) will be the population standard deviation divided by the square root of the sample size. This allows for the construction of confidence intervals and hypothesis testing using z-scores.
What is the sampling distribution of p hat?
The sampling distribution of (\hat{p}) (the sample proportion) describes the distribution of sample proportions obtained from repeated random samples of a given size from a population. It is approximately normal when the sample size is large enough, typically when both (np) and (n(1-p)) are greater than 5, where (p) is the population proportion and (n) is the sample size. The mean of this distribution is equal to the population proportion (p), and the standard deviation (standard error) is given by (\sqrt{\frac{p(1-p)}{n}}).
When the population standard deviation is not know the sampling distribution is a?
When the population standard deviation is not known, the sampling distribution of the sample mean is typically modeled using the t-distribution instead of the normal distribution. This is because the t-distribution accounts for the additional uncertainty introduced by estimating the population standard deviation from the sample. As the sample size increases, the t-distribution approaches the normal distribution, making it more appropriate for larger samples.
What is Confidence Intervals of Standard Error?
The standard deviation associated with a statistic and its sampling distribution.
Statistics HELP Electrical problems affect about 14 percent of new cars an automobile mechanic conducts diagnostic tests on 128 new cars. Describe the sampling distribution for the sample proportion?
Distribution would be centered at .14*128=17.92The standard deviation of the distribution would be root(n(p(p-1)))=root(128*.14*.86)=3.92571013Normal, unimodal
We have a population with mean of 100 and standard deviation of 28 take repeated samples of size 49 and calculate the mean of each sample to form a sampling distribution Is it a Normal Distribution?
a) T or F The sampling distribution will be normal. Explain your answer. b) Find the mean and standard deviation of the sampling distribution. c) We pick one of our samples from the sampling distribution what is the probability that this sample has a mean that is greater than 109 ? Is this a usual or unusual event? these are the rest of the question.
