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emmainna [20.7K]
3 years ago
9

A population has a standard deviation of 5.5. What is the standard error of the sampling distribution if the sample size is 81?

Mathematics
1 answer:
VladimirAG [237]3 years ago
4 0

Answer:

\sigma = 5.5

And we have a sample size of n =81. We want to estimate the standard error of the sampling distribution \bar X and for this case we know that the distribution is given by:

\bar X \sim N(\mu ,\frac{\sigma}{\sqrt{n}})

And the standard error would be:

\sigma_{\bar x}= \frac{\sigma}{\sqrt{n}}

And replacing we got:

\sigma_{\bar x}=\frac{5.5}{\sqrt{81}}= 0.611

Step-by-step explanation:

For this case we know the population deviation given by:

\sigma = 5.5

And we have a sample size of n =81. We want to estimate the standard error of the sampling distribution \bar X and for this case we know that the distribution is given by:

\bar X \sim N(\mu ,\frac{\sigma}{\sqrt{n}})

And the standard error would be:

\sigma_{\bar x}= \frac{\sigma}{\sqrt{n}}

And replacing we got:

\sigma_{\bar x}=\frac{5.5}{\sqrt{81}}= 0.611

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A high school student took two college entrance exams, scoring 1070 on the SAT and 25 on the ACT. Suppose that SAT scores have a
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Answer:

Due to the higher z-score, he did better on the SAT.

Step-by-step explanation:

When the distribution is normal, we use the z-score formula.

In a set with mean \mu and standard deviation \sigma, the zscore of a measure X is given by:

Z = \frac{X - \mu}{\sigma}

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.

Determine which test the student did better on.

He did better on whichever test he had the higher z-score.

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Scored 1070, so X = 1070

SAT scores have a mean of 950 and a standard deviation of 155. This means that \mu = 950, \sigma = 155.

Z = \frac{X - \mu}{\sigma}

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