A randomized trial tested the effectiveness of diets on adults. Among 36 subjects using Diet 1, the mean weight loss after a year was 3.5 pounds with a standard deviation of 5.9 pounds. Among 36 subjects using Diet 2, the mean weight loss after a year was 0.6 pounds with a standard deviation of 4.4 pounds. Construct a 95% confidence interval estimate of the difference between the population means, assuming the population standard deviations are equal.

Respuesta :

Answer:

The 95%  confidence interval is

           [tex] 0.45 <  \mu_1 - \mu_2  < 5.35 [/tex]

Step-by-step explanation:

From the question we are told that

   The first sample size is  [tex]n_1 = 36[/tex]

   The first  sample mean is  [tex]\= x_1 = 3.5[/tex]

   The first standard deviation is  [tex]\sigma_1 = 5.9 \ pounds[/tex]

   The second  sample size is [tex]n_2 = 36[/tex]

    The second  sample mean is  [tex]\= x_2 = 0.6[/tex]

    The second  standard deviation is [tex]\sigma = 4.4[/tex]

Generally the degree of freedom is mathematically represented as

     [tex]df = \frac{ [ \frac{s_1^2 }{n_1 } + \frac{s_2^2 }{n_2} ]^2 }{ \frac{1}{(n_1 - 1 )} [ \frac{s_1^2}{n_1} ]^2 + \frac{1}{(n_2 - 1 )} [ \frac{s_2^2}{n_2} ]^2 }[/tex]

=>  [tex]df = \frac{ [ \frac{5.9^2 }{34 } + \frac{4.4^2 }{34} ]^2 }{ \frac{1}{(34 - 1 )} [ \frac{5.9^2}{34} ]^2 + \frac{1}{(34- 1 )} [ \frac{4.4^2}{ 34} ]^2 }[/tex]

=>  [tex]df =63[/tex]

Generally the standard error is mathematically represented as

      [tex]SE = \sqrt{ \frac{s_1 ^2 }{n_1} + \frac{s_2^2 }{ n_2 } }[/tex]

=>  [tex]SE = \sqrt{ \frac{ 5.9 ^2 }{ 36 } + \frac{ 4.4^2 }{36} }[/tex]

=>  [tex]SE = 1.227[/tex]

From the question we are told the confidence level is  95% , hence the level of significance is    

      [tex]\alpha = (100 - 95 ) \%[/tex]

=>   [tex]\alpha = 0.05[/tex]

Generally from the t distribution table the critical value  of   at a degree of freedom of is  

     [tex]t_{\frac{\alpha }{2}, 63  } =  1.998  [/tex]

Generally the margin of error is mathematically represented as

        [tex]E = t_{\frac{\alpha }{2}, 63 } * SE[/tex]

=>    [tex]E = 1.998 * 1.227[/tex]

=>    [tex]E = 2.45[/tex]

Generally 95% confidence interval is mathematically represented as  

      [tex](\= x_1 - \x_2) -E <  \mu <(\= x_1 - \x_2)  + E[/tex]

 => [tex](3.5  - 0.6) - 2.45 <  \mu_1 - \mu_2  < (  3.5  - 0.6)  + 2.45 [/tex]

=>   [tex] 0.45 <  \mu_1 - \mu_2  < 5.35 [/tex]