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just olya [345]
4 years ago
6

a researcher at a major clinic wishes to estimate the proportion of the adult population of the united states that has sleep dep

rivation. how large a sample is needed in orde to be 98% confident that the sample proprtion will not differ from the true proprtion by more than 5%?
Mathematics
1 answer:
Anna11 [10]4 years ago
5 0

Answer:

The estimate of a population proportion is approximately 541.

Step-by-step explanation:

We can solve the the problem by using the formula for minimum sample needed for interval estimate of a population proportion which is given by the formula

n = pq ((Z/2) / E)^2

As, p is not defined so we use the standard p and q which is 0.5 and 0.5.

The reason for this is we have to choose form 0.1 to 0.9 both values of p and q, we will find the maximum value of pq occurs when they both are 0.5.

Next, we will find the value of (Z/2) by looking at the Z-table, we will find that at 98% confidence (Z/2) = 2.326. Now we start substituting the values in the above formula

n = (0.5)×(0.5) × (2.326/0.05)^2

n = 541.027

n ≅ 541.

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Erika is working on solving the exponential equation 50x = 17; however, she is not quite sure where to start. using complete sen
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The equation be 50x = 17 then the value of x = 17/50.

<h3>How to find the value of x?</h3>

To estimate the value of x, bring the variable to the left side and bring all the remaining values to the right side. Simplify the values to estimate the result.

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2 years ago
Assume that blood pressure readings are normally distributed with a mean of 115 and a standard deviation of 8. If 100 people are
Sergeu [11.5K]

Answer:

D. 0.9938.

Step-by-step explanation:

To solve this question, we need to understand the normal probability distribution and the central limit theorem.

Normal Probability Distribution

Problems of normal distributions can be solved using the z-score formula.

In a set with mean \mu and standard deviation \sigma, the z-score 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 p-value, we get the probability that the value of the measure is greater than X.

Central Limit Theorem

The Central Limit Theorem establishes that, for a normally distributed random variable X, with mean \mu and standard deviation \sigma, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean \mu and standard deviation s = \frac{\sigma}{\sqrt{n}}.

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

Mean of 115 and a standard deviation of 8.

This means that \mu = 115, \sigma = 8

100 people are randomly selected

This means that n = 100, s = \frac{8}{\sqrt{100}} = 0.8

Find the probability that their mean blood pressure will be less than 117.

This is the p-value of Z when X = 117, so:

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

By the Central Limit Theorem

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

Z = \frac{117 - 115}{0.8}

Z = 2.5

Z = 2.5 has a p-value of 0.9938, and thus, the correct answer is given by option D.

8 0
3 years ago
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