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Igoryamba
3 years ago
5

Ms. Scagnetti tried very hard to make sure that nobody was left out during dance class. She thought she had a correct head count

, so she told them to pair up. This didn’t work because there was one person left out. She then told them to get into groups of five, but this didn’t work either because again there was one person left over. So she tried setting up groups of three, but unfortunately there was one left over. Finally, she decided to try groups of four. Again there was one person left out. There are less than 80 students in the dance class. How many were present on that particular day?
Mathematics
1 answer:
frez [133]3 years ago
7 0

no se ingles xd lo siento

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The sample size required is, <em>n</em> = 502.

Step-by-step explanation:

The (1 - <em>α</em>)% confidence interval for population proportion is:

CI=\hat p\pm z_{\alpha/2}\sqrt{\frac{\hat p\cdot (1-\hat p)}{n}}

The margin of error is:

MOE=z_{\alpha/2}\sqrt{\frac{\hat p\ \cdot (1-\hat p)}{n}}

Assume that 50% of the people would support this political candidate.

The margin of error is, MOE = 0.05.

The critical value of <em>z</em> for 97.5% confidence level is:

<em>z</em> = 2.24

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MOE=z_{\alpha/2}\sqrt{\frac{\hat p\ \cdot (1-\hat p)}{n}}

       n=[\frac{z_{\alpha/2}\times \sqrt{\hat p(1-\hat p)}}{MOE}]^{2}

           =[\frac{2.24\times \sqrt{0.50(1-0.50)}}{0.05}]^{2}\\\\=501.76\\\\\approx 502

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The predictive value of a positive test is 18.2%.

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The proportion of the specificity is 70\% \Rightarrow 0.70.70% = 0.70

Step 2 of 2

We have to calculate the probability value of the predictive value of positive test.

\begin{array}{c}\\\left( \begin{array}{l}\\{\rm{Positive Predictive }}\\\\{\rm{value}}\left( {PPV} \right)\\\end{array} \right) = \frac{{{\rm{Prevalence}} \times {\rm{Sensitivity}}}}{{\left( {{\rm{Prevalence}} \times {\rm{Sensitivity}}} \right) + \left( {{\rm{1 - Prevalence}} \times 1 - {\rm{Specificity}}} \right)}}\\\\ = \frac{{0.1 \times 0.60}}{{\left( {0.1 \times 0.60} \right) + \left( {1 - 0.1 \times 1 - 0.70} \right)}}\\\\ = \frac{{0.06}}{{0.33}}\\\\ = 0.181818\\\\ = 0.182{\rm{ }}\left( {{\rm{Round to 3 decimal place}}} \right)\\\end{array}  

(Positive Predictive  value, PPV) =

(Prevalence×Sensitivity)/Prevalence×Sensitivity +(1−Prevalence×1−Specificity)  

=   (0.1×0.60)/0.1×0.60  + (1−0.1×1−0.70) ​  

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(Positive Predictive  value, PPV) = 0.182 (3decimals)    

We have to convert the PPV into percentage,

\begin{array}{c}\\PPV = 0.182 \times 100\\\\ = 18.2\% \\\end{array}  

PPV=0.182×100

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Therefore, the predictive positive value is 18.2%.

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