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Eduardwww [97]
4 years ago
11

A student is considering publishing a new magazine aimed directly at owners of Japanese automobiles. He wanted to estimate the f

raction of cars in the United States that are made in Japan. The computer output below summarizes the results of a random sample of 50 autos. z-interval for proportion With 90.00% confidence 0.29938661 < p(japan) < 0.46984416 a. Interpret the computer output. b. Explain what "90% confidence" means. c. A politician urging consumers to purchase products manufactured in the United States says, "Half of all cars in the United States are made in Japan." Does your confidence interval support or contradict this statement? Explain.
Mathematics
1 answer:
JulsSmile [24]4 years ago
3 0

Answer:

Check Explanation

Step-by-step explanation:

a) Confidence Interval for the population mean is basically an interval of range of values where the true population mean can be found with a certain level of confidence.

Mathematically,

Confidence Interval = (Sample mean) ± (Margin of error)

With p(japan) representing the true population proportion of US automobile that are made in Japan, the computer output 90% confidence

0.29938661 < p(japan) < 0.46984416

mean that p(japan); the true population proportion of US automobile that are made in Japan lies within the range of proportions (0.29938661, 0.46984416) with an assurance level of 90%.

b) 90% confidence mean that the true proportion may or may not be in the given range, but we are 90% certain that it does.

c) The confidence interval contradicts the politician's claim that "Half of all cars in the United States are made in Japan" because the proportion in the politician's claim, (0.50), does not lie within the range of values that our confidence interval says the true population proportion can take on; (0.29938661, 0.46984416).

0.50 lies outside of the confidence interval obtained for the true population proportion of US automobiles that are made in Japan, hence, the confidence interval contradicts the politician's claim.

Hope this Helps!!!

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Nadya [2.5K]

Answer:

exact form: 13/5

Decimal form: 2.6

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3 years ago
A company with a fleet of 150 cars found that the emissions systems of only 4 out of the 25 they tested failed to meet pollution
salantis [7]

Answer:

No, there is no strong evidence that the percentage of the fleet out of compliance is different from their initial thought.

Step-by-step explanation:

We are given that a company with a fleet of 150 cars found that the emissions systems of only 4 out of the 25 they tested failed to meet pollution control guidelines.

The company initially believed that 30% of the fleet was out of compliance.

<u><em>Let p = percentage of the fleet that was out of compliance.</em></u>

SO, Null Hypothesis, H_0 : p = 30%   {means that the percentage of the fleet out of compliance is same as their initial thought}

Alternate Hypothesis, H_A : p \neq 30%   {means that the percentage of the fleet out of compliance is different from their initial thought}

The test statistics that will be used here is <u>One-sample z proportion</u> <u>statistics</u>;

                                 T.S.  = \frac{\hat p-p}{{\sqrt{\frac{\hat p(1-\hat p)}{n} } } } }  ~ N(0,1)

where, \hat p = percentage of the fleet out of compliance = \frac{4}{25} = 16%

           n = sample of systems tested = 25

So, <u><em>test statistics</em></u>  =  \frac{0.16-0.30}{{\sqrt{\frac{0.16(1-0.16)}{25} } } } }

                              =  -1.909

The value of the test statistics is -1.909.

<em>Since in the question we are not given with the level of significance at which hypothesis can be tested, so we assume it to be 5%. Now at 5% significance level, </em><u><em>the z table gives critical values between -1.96 and 1.96 for two-tailed test.</em></u><em> </em>

<em>Since our test statistics lies within the range of critical values of z, so we have insufficient evidence to reject our null hypothesis as it will not fall in the rejection region due to which we fail to reject our null hypothesis.</em>

Therefore, we conclude that the percentage of the fleet out of compliance is same as their initial thought.

3 0
3 years ago
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