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Vika [28.1K]
2 years ago
7

A company considers buying a machine to manufacture a certain item. When tested, 28 out of 600 items produccd by the machine wer

e found defective. Do the data support the hypothesis that the defect rate of the machine is smaller than 3%, at the 5% significance level?
H0:p≥0.03
Ha:p<0.03
α=0.05
Critical value z=−1.645
Reject H0 if z<−1.645
Test statistic
⇒Z0=X¯¯¯¯¯−μoσ/n√=>0.0467−0.030.03∗0.97/600√=14.057
Therefore, we fail to reject H0. There isn't enough evidence to say that defect rate of machine is smaller than 3%.
Mathematics
1 answer:
weqwewe [10]2 years ago
7 0

Answer:

The p-value of the test is 0.9918 > 0.05, which means that we fail to reject H_0, as we do not have enough evidence to say that defect rate of machine is smaller than 3%.

Step-by-step explanation:

The null and alternate hypothesis are:

H0:p≥0.03

Ha:p<0.03

The test statistic is:

z = \frac{X - \mu}{\frac{\sigma}{\sqrt{n}}}

In which X is the sample mean, \mu is the value tested at the null hypothesis, \sigma is the standard deviation and n is the size of the sample.

0.03 is tested at the null hypothesis:

This means that \mu = 0.03, \sigma = \sqrt{0.03*0.97}

28 out of 600 items produced by the machine were found defective.

This means that n = 600, X = \frac{28}{600} = 0.0467

Value of the test-statistic:

z = \frac{X - \mu}{\frac{\sigma}{\sqrt{n}}}

z = \frac{0.0467 - 0.03}{\frac{\sqrt{0.03*0.97}}{\sqrt{600}}}

z = 2.4

P-value of the test:

The p-value of the test is the probability of finding a sample proportion below 0.0467, which is the p-value of z = 2.4.

Looking at the z-table, z = 2.4 has a p-value of 0.9918.

The p-value of the test is 0.9918 > 0.05, which means that we fail to reject H_0, as we do not have enough evidence to say that defect rate of machine is smaller than 3%.

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