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scoundrel [369]
3 years ago
8

In January 2002, two students made worldwide headlines by spinning a Belgian euro 250 times and getting 140 heads—that’s 56%. Th

at makes the 90% confidence interval (51%, 61%). What does this mean? Are these conclusions correct? Explain.
Mathematics
1 answer:
natita [175]3 years ago
6 0

Answer with explanation:

The 90% confidence interval (51%, 61%) for proportion means that the proportion of getting heads lie in it.

Given : Total number of times coin is tossed = 250

Number of times they got head =140

The probability of getting a head = 0.56

The confidence interval for proportion is given by :-

p\pm z_{\alpha/2}\sqrt{\dfrac{p(1-p)}{n}}

Given significance level : \alpha=1-0.90=0.1

Critical value : z_{\alpha/2}=z_{0.05}=\pm1.645

Now, the 90​% confidence interval for proportion will be :-

0.56\pm (1.645)\sqrt{\dfrac{0.56(1-0.56)}{250}}\approx0.56\pm 0.0516\\\\=(0.56-0.0516,0.56+0.0516)=(0.5084,\ 0.6116)\approx(51\%,\ 61\%)

Hence, the given confidence interval is correct.

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To estimate the mean height μ of male students on your campus,you will measure an SRS of students. You know from government data
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Answer:

a) \sigma = 0.167

b) We need a sample of at least 282 young men.

Step-by-step explanation:

Problems of normally distributed samples can be 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}

This Zscore is how many standard deviations the value of the measure X 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.

(a) What standard deviation must x have so that 99.7% of allsamples give an x within one-half inch of μ?

To solve this problem, we use the 68-95-99.7 rule. This rule states that:

68% of the measures are within 1 standard deviation of the mean.

95% of the measures are within 2 standard deviations of the mean.

99.7% of the measures are within 3 standard deviations of the mean.

In this problem, we want 99.7% of all samples give X within one-half inch of \mu. So X - \mu = 0.5 must have Z = 3 and X - \mu = -0.5 must have Z = -3.

So

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

3 = \frac{0.5}{\sigma}

3\sigma = 0.5

\sigma = \frac{0.5}{3}

\sigma = 0.167

(b) How large an SRS do you need to reduce the standard deviationof x to the value you found in part (a)?

You know from government data that heights of young men are approximately Normal with standard deviation about 2.8 inches. This means that \sigma = 2.8

The standard deviation of a sample of n young man is given by the following formula

s = \frac{\sigma}{\sqrt{n}}

We want to have s = 0.167

0.167 = \frac{2.8}{\sqrt{n}}

0.167\sqrt{n} = 2.8

\sqrt{n} = \frac{2.8}{0.167}

\sqrt{n} = 16.77

\sqrt{n}^{2} = 16.77^{2}

n = 281.23

We need a sample of at least 282 young men.

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