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UkoKoshka [18]
4 years ago
15

A public bus company official claims that the mean waiting time for bus number 14 during peak hours is less than 10 minutes. Kar

en took bus number 14 during peak hours on 18 different occasions. Her mean waiting time was 7.8 minutes with a standard deviation of 2.5 minutes. At the 0.01 significance level, test the claim that the mean is less than 10 minutes.
Mathematics
1 answer:
ch4aika [34]4 years ago
5 0

Answer:

We conclude that the mean waiting time is less than 10 minutes.

Step-by-step explanation:

We are given that a public bus company official claims that the mean waiting time for bus number 14 during peak hours is less than 10 minutes.

Karen took bus number 14 during peak hours on 18 different occasions. Her mean waiting time was 7.8 minutes with a standard deviation of 2.5 minutes.

Let \mu = <u><em>mean waiting time for bus number 14.</em></u>

So, Null Hypothesis, H_0 : \mu \geq 10 minutes      {means that the mean waiting time is more than or equal to 10 minutes}

Alternate Hypothesis, H_A : \mu < 10 minutes    {means that the mean waiting time is less than 10 minutes}

The test statistics that would be used here <u>One-sample t test statistics</u> as we don't know about the population standard deviation;

                       T.S. =  \frac{\bar X-\mu}{\frac{s}{\sqrt{n} } }  ~ t_n_-_1

where, \bar X = sample mean waiting time = 7.8 minutes

             s = sample standard deviation = 2.5 minutes

             n = sample of different occasions = 18

So, <u><em>test statistics</em></u> =  \frac{7.8-10}{\frac{2.5}{\sqrt{18} } }  ~ t_1_7

                              =  -3.734

The value of t test statistics is -3.734.

Now, at 0.01 significance level the t table gives critical value of -2.567 for left-tailed test.

Since our test statistic is less than the critical value of t as -3.734 < -2.567, so we have sufficient evidence to reject our null hypothesis as it will fall in the rejection region due to which <u>we reject our null hypothesis</u>.

Therefore, we conclude that the mean waiting time is less than 10 minutes.

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0.004376634...

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that completely depends on the circumstances.

what was the requirement about max. faulty rate in the first place ? if it was 2%, then the engineer's approach is basically sound.

it then further depends what are the costs resulting from a faulty unit ? that depends again on when the defect is usually found (still in manufacturing, or already out there at the customer site, or somewhere in between) and how critical the product containing such transistors is. e.g. recalls for products are extremely costly, while simply sorting the bad transistors out during the manufacturing process can be rather cheap. if there is a reliable and quick process to do so.

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