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Vlad [161]
3 years ago
12

A recipe uses 6 cups of cheese to serve 30 people. How much cheese is needed for 50 people

Mathematics
1 answer:
yanalaym [24]3 years ago
7 0
\bf \begin{array}{ccll}
\stackrel{cheese}{cups}&people\\
\text{\textemdash\textemdash\textemdash}&\text{\textemdash\textemdash\textemdash}\\
6&30\\
c&50
\end{array}\implies \cfrac{6}{c}=\cfrac{30}{50}\implies \cfrac{6\cdot 50}{30}=c
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Answer:

Step-by-step explanation:

Hello!

The objective is to test ESP, for this, a psychic was presented with cards face down and asked to determine if each of the cards was one of four symbols: a star, cross, circle, square.

Be X: number of times the psychic identifies the symbols on the cards correctly is a size n sample.

p the probability that the psychic identified the symbol on the cards correctly

You have to calculate the sample size n to estimate the proportion with a confidence level of 95% and a margin of error of d=0.01

The CI for the population proportion is constructed "sample proportion" ± "margin of error" Symbolically:

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Where  d= Z_{1-\alpha /2} * (\sqrt{\frac{p'(1-p')}{n} } ) is the margin of error. As you can see, the formula contains the sample proportion (it is normally symbolized p-hat, in this explanation I'll continue to symbolize it p'), you have to do the following consideration:

Every time the psychic has to identify a card he can make two choices:

"Success" he identifies the card correctly

"Failure" he does not identify the card correctly

If we assume that each symbol has the same probability of being chosen at random P(star)=P(cross)=P(circle)=P(square)= 1/4= 0.25

Let's say, for example, that the card has the star symbol.

The probability of identifying it correctly will be P(success)= P(star)= 1/4= 0.25

And the probability of not identifying it correctly will be P(failure)= P(cross) + P(circle) + P(square)= 1/4 + 1/4 + 1/4= 3/4= 0.75

So for this experiment, we'll assume the "worst case scenario" and use p'= 1/4 as the estimated probability of the psychic identifying the symbol on the card correctly.

The value of Z will be Z_{1-\alpha /2}= Z_{0.975}= 1.96

Now using the formula you have to clear the sample size:

d= Z_{1-\alpha /2} * (\sqrt{\frac{p'(1-p')}{n} } )

\frac{d}{Z_{1-\alpha /2}} = \sqrt{\frac{p'(1-p')}{n} }

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n = p'(1-p')*(\frac{Z_{1-\alpha /2}}{d})^2

n = (0.25*0.75)*(\frac{1.96}{0.01})^2= 7203

To estimate p with a margin of error of 0.01 and a 95% confidence level you have to take a sample of 7203 cards.

I hope this helps!

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