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alina1380 [7]
2 years ago
13

Issac, BYU-Idaho student, found an old article in the school paper, the Scroll, that asserted that 11% of girls "wait for their

missionary". Now that some years have passed and the missionary age limits have changed, and Isaac wants to revisit the question and would like to estimate what proportion of girls "wait for their missionary". If he is willing to accept a margin of error of 3%, and a 90% confidence level, how many observations does he need in his sample
Mathematics
1 answer:
ololo11 [35]2 years ago
8 0

Answer: 151

Step-by-step explanation:

When the prior estimate of population proportion is available , then the formula for sample size:  n=p(1-p)(\dfrac{z^*}{E})^2

, where p= prior estimate of population proportion

z*= critical-value.

E= Margin of  error.

Let p be the proportion of of girls "wait for their missionary".

p = 11% =0.11

E= ± 0.03

The critical z-value corresponding to 90% confidence level = z*=1.645 [using z-table ]

Substitute all the values in the above formula , we get

Required sample size  :n=(0.11)(1-0.11)(\dfrac{(1.96)}{0.05})^2

\Rightarrow\ n=(0.11)(0.89)(39.2)^2

\Rightarrow\ n=(0.0979)(1536.64)\\\\\Rightarrow\ n=150.437056\approx151 [Rounded to next integer.]

Thus, the number of observations he needs in his sample = 151

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AC : BC = AQ : PQ

AC = BC AQ / PQ

AC = 12.6 (7.2) / 8.4

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Answer: 10.8 cm

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He generates a random whole number from 1 to 3.

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Each winner has 3 possibilities, gets cotton candy, gets a shirt, or gets a keychain. We can asign each of this possibiltiies a number, 1 for cotton candy, 2 for the shirt and 3 for a keychain. So, for a simulation, its enough to take one of this whole numbers for each winner.

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7 0
2 years ago
A Roper survey reported that 65 out of 500 women ages 18-29 said that they had the most say when purchasing a computer; a sample
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Answer:

Step-by-step explanation:

<u><em>Step(i):-</em></u>

<em>Given first random sample size n₁ = 500</em>

Given  Roper survey reported that 65 out of 500 women ages 18-29 said that they had the most say when purchasing a computer.

<em>First sample proportion </em>

<em>                              </em>p^{-} _{1} = \frac{65}{500} = 0.13

<em>Given second sample size n₂ = 700</em>

<em>Given a sample of 700 men (unrelated to the women) ages 18-29 found that 133 men said that they had the most say when purchasing a computer.</em>

<em>second sample proportion </em>

<em>                              </em>p^{-} _{2} = \frac{133}{700} = 0.19

<em>Level of significance = α = 0.05</em>

<em>critical value = 1.96</em>

<u><em>Step(ii)</em></u><em>:-</em>

<em>Null hypothesis : H₀: There  is no significance difference between these proportions</em>

<em>Alternative Hypothesis :H₁: There  is significance difference between these proportions</em>

<em>Test statistic </em>

<em></em>Z = \frac{p_{1} ^{-}-p^{-} _{2}  }{\sqrt{PQ(\frac{1}{n_{1} } +\frac{1}{n_{2} } )} }<em></em>

<em>where </em>

<em>         </em>P = \frac{n_{1} p^{-} _{1}+n_{2} p^{-} _{2}  }{n_{1}+ n_{2}  } = \frac{500 X 0.13+700 X0.19  }{500 + 700 } = 0.165<em></em>

<em>        Q = 1 - P = 1 - 0.165 = 0.835</em>

<em></em>Z = \frac{0.13-0.19  }{\sqrt{0.165 X0.835(\frac{1}{500 } +\frac{1}{700 } )} }<em></em>

<em>Z =  -2.76</em>

<em>|Z| = |-2.76| = 2.76 > 1.96 at 0.05 level of significance</em>

<em>Null hypothesis is rejected at 0.05 level of significance</em>

<em>Alternative hypothesis is accepted at 0.05 level of significance</em>

<u><em>Conclusion:</em></u><em>-</em>

<em>There is there is a difference between these proportions at α = 0.05</em>

3 0
2 years ago
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