A group of engineers developed a new design for a steel cable. They need to estimate the amount of weight the cable can hold. The weight limit will be reported on cable packaging. The engineers take a random sample of 48 cables and apply weights to each of them until they break. The 48 cables have a mean breaking weight of 773 lb. The standard deviation of the breaking weight for the sample is 16.1 lb. Find the 95% confidence interval to estimate the mean breaking weight for this type cable.

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Answer:

The 95%   confidence interval is   [tex]768.44 < \mu <777.55[/tex]

Step-by-step explanation:

From the question we are told that  

    The  sample size is n = 48

    The sample mean is  [tex]\= x = 773 \ lb[/tex]

     The standard deviation is  [tex]\sigma = 16.1 \ lb[/tex]

   

Now given that the confidence level is  95% , then the level of significance is mathematically represented as

          [tex]\alpha = 100 - 95[/tex]

          [tex]\alpha = 5 \%[/tex]

          [tex]\alpha = 0.05[/tex]

Next we obtain the  critical value of  [tex]\frac{\alpha }{2}[/tex] from the normal distribution table , the value is

              [tex]Z_{\frac{\alpha }{2} } = 1.96[/tex]

The reason we are obtaining critical values of   [tex]\frac{\alpha }{2}[/tex] instead of    [tex]\alpha[/tex] is because  

[tex]\alpha[/tex] represents the area under the normal curve where the confidence level interval (   [tex]1-\alpha[/tex] ) did not cover which include both the left and right tail while

[tex]\frac{\alpha }{2}[/tex]is just the area of one tail which what we required to calculate the margin of error

 The  margin of error is mathematically represented as

      [tex]MOE = Z_{\frac{\alpha }{2} } * \frac{\sigma }{ \sqrt{n} }[/tex]

substituting values

     [tex]MOE = 1.96 * \frac{ 16.1 }{ \sqrt{48} }[/tex]

     [tex]MOE = 4.555[/tex]

The 95% confidence interval to estimate the mean breaking weight for this type cable is mathematically evaluated as

      [tex]\= x - MOE < \mu < \= x - MOE[/tex]

substituting values

    [tex]773 - 4.555 < \mu < 773 + 4.555[/tex]

     [tex]768.44 < \mu <777.55[/tex]

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