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AVprozaik [17]
2 years ago
5

The number of surface flaws in a plastic roll used for auto interiors follows a Poisson distribution with a mean of 0.05 flaw pe

r square foot . Each car contains 10 ft2 of the plastic roll and ten (10) of the cars are sold to a particular rental agency. a) What is the probability that there are no flaws in a given car’s interior
Mathematics
1 answer:
ElenaW [278]2 years ago
5 0

Answer:

0.6065

Step-by-step explanation:

Probability mass function of probability distribution : P(X=x)=\frac{e^{-\lambda} \times \lambda^x}{x !}

a mean of 0.05 flaw per square foot

Each car contains 10 sq.feet of the plastic roll

Mean = 0.05

Mean = \lambda = 0.05 \times 10=0.5

We are supposed to find What is the probability that there are no flaws in a given car’s interior i.e,P(X=0)

Substitute the value in the formula

P(X=0)=\frac{e^{-0.5} \times (0.5)^0x}{0 !}

P(X=0)=\frac{e^{-0.5} \times (0.5)^0}{1}

P(X=0)=0.6065

Hence the probability that there are no flaws in a given car’s interior is 0.6065

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Jack is a college athlete who has been weighing himself weekly on the same scale in the athletic center for the past few years.
Radda [10]

Answer:

a) Since the Confidence is 0.90 or 90%, the value of \alpha=0.1 and \alpha/2 =0.05, and we can use excel, a calculator or a table to find the critical value. The excel command would be: "=-NORM.INV(0.05,0,1)".And we see that z_{\alpha/2}=\pm 1.64

b) \bar X \sim N(\mu ,\frac{\sigma}{\sqrt{n}})

And the standard error is given by:

SE = \frac{\sigma}{\sqrt{n}}=\frac{3}{\sqrt{9}}=1

c) \bar X \pm t_{\alpha/2}\frac{s}{\sqrt{n}}   (1)

And the margin of error is:

ME= z_{\alpha/2} \frac{\sigma}{\sqrt{n}} = 1.64

And then the confidence interval is be given by:

200-1.64 = 198.36

200+1.64 = 201.64

Step-by-step explanation:

Previous concepts

A confidence interval is "a range of values that’s likely to include a population value with a certain degree of confidence. It is often expressed a % whereby a population means lies between an upper and lower interval".

The margin of error is the range of values below and above the sample statistic in a confidence interval.

Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".

\bar X= 200 represent the sample mean

\mu population mean (variable of interest)

\sigma=3 represent the population standard deviation

n=9 represent the sample size  

Part a

Since the Confidence is 0.90 or 90%, the value of \alpha=0.1 and \alpha/2 =0.05, and we can use excel, a calculator or a table to find the critical value. The excel command would be: "=-NORM.INV(0.05,0,1)".And we see that z_{\alpha/2}=\pm 1.64

Part b

The distribution for the sample mean is given by:

\bar X \sim N(\mu ,\frac{\sigma}{\sqrt{n}})

And the standard error is given by:

SE = \frac{\sigma}{\sqrt{n}}=\frac{3}{\sqrt{9}}=1

Part c

The confidence interval for the mean is given by the following formula:

\bar X \pm t_{\alpha/2}\frac{s}{\sqrt{n}}   (1)

And the margin of error is:

ME= z_{\alpha/2} \frac{\sigma}{\sqrt{n}} = 1.64

And then the confidence interval is be given by:

200-1.64 = 198.36

200+1.64 = 201.64

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