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umka2103 [35]
1 year ago
11

The average lifetime of a certain new cell phone is 3.4 years. The manufacturer will replace any cell phone failing within three

years of the date of purchase. The lifetime of these cell phones is known to follow an exponential distribution. 68% of these phone last how long (in years)?
Mathematics
1 answer:
melisa1 [442]1 year ago
4 0

Answer:

68% of these phones last 3.87 years.

Step-by-step explanation:

Exponential distribution:

The exponential probability distribution, with mean m, is described by the following equation:

f(x) = \mu e^{-\mu x}

In which \mu = \frac{1}{m} is the decay parameter.

The probability that x is lower or equal to a is given by:

P(X \leq x) = \int\limits^a_0 {f(x)} \, dx

Which has the following solution:

P(X \leq x) = 1 - e^{-\mu x}

The probability of finding a value higher than x is:

P(X > x) = 1 - P(X \leq x) = 1 - (1 - e^{-\mu x}) = e^{-\mu x}

The average lifetime of a certain new cell phone is 3.4 years.

This means that m = 3.4, \mu = \frac{1}{3.4} = 0.2941

So

P(X \leq x) = 1 - e^{-0.2941x}

68% of these phones last how long (in years)?

This is x for which:

P(X \leq x) = 0.68

P(X \leq x) = 1 - e^{-0.2941x}

Then

0.68 = 1 - e^{-0.2941x}

e{-0.2941x} = 0.32

\ln{e{-0.2941x}} = \ln{0.32}

-0.2941x = \ln{0.32}

x = -\frac{\ln{0.32}}{0.2941}

x = 3.87

68% of these phones last 3.87 years.

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Answer:

1.667-2.31\frac{1.803}{\sqrt{9}}=0.2789  

1.667+2.31\frac{1.803}{\sqrt{9}}=3.055  

So on this case the 95% confidence interval would be given by (0.2789;3.055)  

The 95% confidence interval to judge whether the two indeners result in different measurements is?

Yes the confidence interval not contains the value 0 so we can conclude that the values for Diamond are significantly higher than the values for Steel Ball at 5% of significance.

Step-by-step explanation:

We have the following dataset:

specimen    1     2    3     4      5     6     7    8     9

Steel Ball   51   57   61   70   68   54   65  51   53

Diamond   53   55  63   74   69   56   68  51   56

If we calculate the differences diamond-steel ball we have this datase:

d: 2, -2, 2, 4, 1, 2, 3, 0, 3

The second step is calculate the mean difference  

\bar d= \frac{\sum_{i=1}^n d_i}{n}=1.667

The third step would be calculate the standard deviation for the differences, and we got:

s_d =\frac{\sum_{i=1}^n (d_i -\bar d)^2}{n-1} =1.803

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".  

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

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

In order to calculate the critical value t_{\alpha/2} we need to find first the degrees of freedom, given by:  

df=n-1=9-1=8  

Since the confidence is 0.95 or 95%, the value of \alpha=0.05 and \alpha/2 =0.025, and we can use excel, a calculator or a table to find the critical value. The excel command would be: "=-T.INV(0.025,9)".And we see that t_{\alpha/2}=2.31.

Now we have everything in order to replace into formula (1):  

1.667-2.31\frac{1.803}{\sqrt{9}}=0.2789  

1.667+2.31\frac{1.803}{\sqrt{9}}=3.055  

So on this case the 95% confidence interval would be given by (0.2789;3.055)  

The 95% confidence interval to judge whether the two indeners result in different measurements is?

Yes the confidence interval not contains the value 0 so we can conclude that the values for Diamond are significantly higher than the values for Steel Ball at 5% of significance.

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