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Assoli18 [71]
2 years ago
3

Suppose that 65% of all dialysis patients will survive for at least 5 years. In a simple random sample of 100 new dialysis patie

nts, what is the probability that the proportion surviving for at least five years will exceed 80%, rounded to 5 decimal places?
Mathematics
1 answer:
agasfer [191]2 years ago
5 0

The probability that the proportion surviving for at least five years

will exceed 80% is 0.00084

Step-by-step explanation:

The given is:

1. Suppose that 65% of all dialysis patients will survive for at least

   5 years

2. A random sample has 100 new dialysis patients

We need to find the probability that the proportion surviving for at

least five years will exceed 80%

At first find σ from the rule below

∵ σ = \sqrt{\frac{P(1-P)}{n}}

∵ P = 65% = 0.65

∵ n = 100

∴ σ = \sqrt{\frac{0.65(1-0.65)}{100}}

∴ σ = 0.04770

Now find z-score from the rule:

∵ z = (x - μ)/σ

∵ x = 80% = 0.80

∵ μ = P = 0.65

∵ σ = 0.04770

- Substitute these values in the rule

∴ z = \frac{0.80-0.65}{0.04770} = 3.14

Use the normal distribution table for z-score to find the

corresponding area of z = 3.14

∵ The corresponding area is 0.99916

∵ For P(x > 80%) the area to the right is needed

∵ P(x > 80%) = 1 - 0.99916

∴ P(x > 80%) = 0.00084

The probability that the proportion surviving for at least five years

will exceed 80% is 0.00084

Learn more:

You can learn more about the random sample in brainly.com/question/5510873

#LearnwithBrainly

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The function f(x)=tan(3/2x-pi/2) has:
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Which graph shows the solution to the system of linear inequalities?
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Answer:

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Step-by-step explanation:

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Y Intercept :

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Given: Quadrilateral ABCD is a kite.
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Answer:


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One

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Two

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Three

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2 years ago
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The inside diameter of a randomly selected piston ring is a random variable with mean value 13 cm and standard deviation 0.08 cm
sweet-ann [11.9K]

Answer:

a) P(12.99 ≤ X ≤ 13.01) = 0.3840

b) P(X ≥ 13.01) = 0.3075

Step-by-step explanation:

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

Normal probability distribution

Problems of normally distributed samples are solved using 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.

Central Limit Theorem

The Central Limit Theorem estabilishes 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.

In this problem, we have that:

\mu = 13, \sigma = 0.08

(a) Calculate P(12.99 ≤ X ≤ 13.01) when n = 16.

Here we have n = 16, s = \frac{0.08}{\sqrt{16}} = 0.02

This probability is the pvalue of Z when X = 13.01 subtracted by the pvalue of Z when X = 12.99.

X = 13.01

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

By the Central Limit Theorem

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

Z = \frac{13.01 - 13}{0.02}

Z = 0.5

Z = 0.5 has a pvalue of 0.6915

X = 12.99

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

Z = \frac{12.99 - 13}{0.02}

Z = -0.5

Z = -0.5 has a pvalue of 0.3075

0.6915 - 0.3075 = 0.3840

P(12.99 ≤ X ≤ 13.01) = 0.3840

(b) How likely is it that the sample mean diameter exceeds 13.01 when n = 25?

P(X ≥ 13.01) =

This is 1 subtracted by the pvalue of Z when X = 13.01. So

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

Z = \frac{13.01 - 13}{0.02}

Z = 0.5

Z = 0.5 has a pvalue of 0.6915

1 - 0.6915 = 0.3075

P(X ≥ 13.01) = 0.3075

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2 years ago
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