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A variable X is described by a semi-circular density curve with mean 0 and standard deviation 0.4, as shown below:We take a simple random sample of 1000 individuals from the semi-circular distribution and calculate the sample mean x ̄(x-bar). The sampling distribution of X ̄(x-bar) is:Question 6Answera.semi-circular with mean 0 and standard deviation 0.0126.b.semi-circular with mean 0 and standard deviation 0.004.c.approximately normal with mean 0 and standard deviation 0.004.d.approximately normal with mean 0 and standard deviation 0.4.e.approximately normal with mean 0 and standard deviation 0.0126.

Question

A variable X is described by a semi-circular density curve with mean 0 and standard deviation 0.4, as shown below:We take a simple random sample of 1000 individuals from the semi-circular distribution and calculate the sample mean x ̄(x-bar). The sampling distribution of X ̄(x-bar) is:Question 6Answera.semi-circular with mean 0 and standard deviation 0.0126.b.semi-circular with mean 0 and standard deviation 0.004.c.approximately normal with mean 0 and standard deviation 0.004.d.approximately normal with mean 0 and standard deviation 0.4.e.approximately normal with mean 0 and standard deviation 0.0126.

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Solution

The sampling distribution of the sample mean (x-bar) will be approximately normal due to the Central Limit Theorem, which states that if you have a population with mean μ and standard deviation σ and take sufficiently large random samples from the population with replacement, then the distribution of the sample means will be approximately normally distributed. This will hold true regardless of whether the source population is normal or skewed, provided the sample size is sufficiently large (usually n > 30).

In this case, the mean of the sampling distribution (x-bar) will be the same as the population mean, which is 0.

The standard deviation of the sampling distribution (often called the standard error) is the standard deviation of the population divided by the square root of the sample size. In this case, that's 0.4 divided by the square root of 1000, which is approximately 0.0126.

So, the correct answer is:

e. approximately normal with mean 0 and standard deviation 0.0126.

This problem has been solved

Similar Questions

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Which of the following statements about the sampling distribution of the sample mean, x-bar, is true? Check all that apply. The distribution is normal regardless of the shape of the population distribution, as long as the sample size, n, is large enough. The distribution is normal regardless of the sample size, as long as the population distribution is normal. The distribution's mean is the same as the population mean. The distribution's standard deviation is smaller than the population standard deviation.

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Pictured below (in scrambled order) are three histograms. One of them represents a population distribution. The other two are sampling distributions of x-bar: one for sample size n = 5 and one for sample size n = 30.Based on the histograms, what is the most likely value of the population mean? 0.5 3.0 4.5 7.5 350

Question 6Typically the x-axis of a bar graph shows1 pointfrequency.the values of the variable of interest.percent.the distribution.

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