Environmental engineers are using data collected by weather data centers to learn how climate affects the sea ice. Of ice melt ponds studied in a certain​ region, were classified as having​ "first-year ice". The researchers estimated that about ​% of melt ponds in the region have​ first-year ice.​ Estimate, with​ 90% confidence, the percentage of all​ ice-melt ponds in the region that have​ first-year ice. Give a practical interpretation of the results.

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Complete Question

Environmental engineers are using data collected by weather data centers to learn how climate affects the sea ice. Of 526  ice melt ponds studied in a certain​ region, 84 were classified as having​ "first-year ice". The researchers estimated that about 16% of melt ponds in the region have​ first-year ice.​ Estimate, with​ 90% confidence, the percentage of all​ ice-melt ponds in the region that have​ first-year ice. Give a practical interpretation of the results.

Answer:

The 90% confidence interval is [tex] 0.1337   <  p < 0.1857   [/tex]

Step-by-step explanation:

From the question we are told that

   The sample size is  n  =  526  

   The  number that were classified to having a 'first-year ice ' is  k =  84

    The population proportion is  p  = 0.16

Generally the sample proportion is mathematically represented as

         [tex]\^ p = \frac{k}{ n }[/tex]

=>      [tex]\^ p = \frac{ 84}{ 526 }[/tex]

=>      [tex]\^ p = 0.1597[/tex]

From the question we are told the confidence level is  90% , hence the level of significance is    

      [tex]\alpha = (100 - 90 ) \%[/tex]

=>   [tex]\alpha = 0.10[/tex]

Generally from the normal distribution table the critical value  of  [tex]\frac{\alpha }{2}[/tex] is  

   [tex]Z_{\frac{\alpha }{2} } =  1.645[/tex]

Generally the margin of error is mathematically represented as  

     [tex]E =  Z_{\frac{\alpha }{2} } * \sqrt{\frac{ p (1-  p)}{n} } [/tex]

=>   [tex]E =  1.645 * \sqrt{\frac{0.16 (1- 0.16)}{ 526} } [/tex]

=>  [tex]E =  0.026 [/tex]

Generally 95% confidence interval is mathematically represented as  

      [tex]\^ p -E <  p <  \^ p +E[/tex]

=>   [tex]0.1597  -0.026  <  p < 0.1597  -0.026  [/tex]

=>   [tex] 0.1337   <  p < 0.1857   [/tex]