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What else can I help you with?
The mean of a sampling distribution is equal to the mean of the underlying population?
This is the Central Limit Theorem.
When the population standard deviation is unknown the sampling distribution is equal to what?
The answer will depend on the underlying distribution for the variable. You may not simply assume that the distribution is normal.
What is the distribution of values taken by a statistic in all possible samples of equal size from the same population?
It is the sampling distribution of that variable.
A sample of 24 observations is taken from a population that has 150 elements The sampling distribution of the mean is?
A sample of 24 observations is taken from a population that has 150 elements. The sampling distribution of is
When may the sampling distribution of x̅ be considered to be approximately normal?
the standard deviation of the population(sigma)/square root of sampling mean(n)
The mean of a sampling distribution is equal to the mean of the underlying population?
This is the Central Limit Theorem.
What will the sampling distribution of the mean be if a population is normally distribution?
Also normally distributed.
What is sampling distribution of the mean?
Thanks to the Central Limit Theorem, the sampling distribution of the mean is Gaussian (normal) whose mean is the population mean and whose standard deviation is the sample standard error.
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.
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.
The distribution of sample means consists of?
A set of probabilities over the sampling distribution of the mean.
Is the standard deviation of the sampling distribution of the sample mean is o?
NO
How do you calculate the mean of the sampling distribution of the sample proportion?
i dont no the answer
When the population standard deviation is unknown the sampling distribution is equal to what?
The answer will depend on the underlying distribution for the variable. You may not simply assume that the distribution is normal.
What will be the sampling distribution of the mean for a sample size of one?
It will be the same as the distribution of the random variable itself.
What is the distribution of values taken by a statistic in all possible samples of equal size from the same population?
It is the sampling distribution of that variable.
Will the mean and median in a symmetric distribution always be equal or approximately equal and Why?
In a symmetric distribution, the mean and median will always be equal. This is because symmetry implies that the distribution is balanced around a central point, which is where both the mean (the average) and the median (the middle value) will fall. Therefore, in perfectly symmetric distributions like the normal distribution, the mean, median, and mode coincide at the center. In practice, they may be approximately equal in symmetric distributions that are not perfectly symmetrical due to rounding or sampling variability.
