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Kipish [7]
2 years ago
14

High-power experimental engines are being developed by the Stevens Motor Company for use in its new sports coupe. The engineers

have calculated the maximum horsepower for the engine to be 600 HP. Sixteen engines are randomly selected for horsepower testing. The sample has an average maximum HP of 620 with a standard deviation of 45 HP. Calculate a 95% confidence interval for average maximum HP. Round your answer to one decimal place. (Answer: 595.5 to 644.5)
Mathematics
1 answer:
mamaluj [8]2 years ago
7 0

Answer:

The 95% confidence interval the average maximum power is (596.0 to 644.0)

Step-by-step explanation:

Average maximum of the sample = x = 620 HP

Standard Deviation = s = 45 HP

Sample size = n = 16

We have to calculate the 95% confidence interval. The value of Population standard deviation is unknown, and value of sample standard deviation is known. Therefore, we will use one sample t-test to build the confidence interval.

Degrees of freedom = df = n - 1 = 15

Critical t-value associated with 95% confidence interval and 15 degrees of freedom, as seen from t-table = t_{\frac{\alpha}{2}} = 2.131

The formula to calculate the confidence interval is:

(x-t_{\frac{\alpha}{2} } \times \frac{s}{\sqrt{n} }, x+t_{\frac{\alpha}{2} } \times \frac{s}{\sqrt{n} })

We have all the required values. Substituting them in the above expression, we get:

(620-2.131 \times \frac{45}{\sqrt{16} }, 620+2.131 \times \frac{45}{\sqrt{16} })\\\\ =(596.0 , 644.0)

Thus, the 95% confidence interval the average maximum power is (596.0 to 644.0)

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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>

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<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>

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