Suppose a local manufacturing company claims their production line has a variance of less than 9.0. A quality control engineer decides to test this claim by sampling 35 parts. She finds that the standard deviation of the sample is 2.12. Is this enough evidence at the 1% level of significance, to accept the manufacturing companies claim? Calculate the appropriate test statistic (round to 2 decimal places as needed)

Answer :

Answer:

The decision rule is  

   Fail to reject the null hypothesis

The conclusion is  

   There is no sufficient evidence to accept  the manufacturing company claims

Step-by-step explanation:

From the question we are told that

   The sample size is  n =  35

   The sample standard deviation is  [tex]s =  2.12[/tex]

   The level of significance is [tex]\alpha = 0.01[/tex]

The null hypothesis is  [tex]H_o  :  \sigma ^2  = 9.0[/tex]

The alternative hypothesis is  [tex]H_a  :  \sigma ^2  <  9.0[/tex]

Gnerally the test statistics is mathematically represented as

    [tex]X^2 _{stat} =  \frac{(n -1) * s^2 }{\sigma^2 }[/tex]

    [tex]X^2 _{stat} =  \frac{(35  -1) * 2.12^2 }{9 }[/tex]

=> [tex]X^2 _{stat} =  16.98[/tex]

Generally the degree of freedom is mathematically represented as

   [tex]df =  n - 1[/tex]

=>    [tex]df =  35 - 1[/tex]

=>    [tex]df =  34[/tex]

From the chi - distribution table the  critical value of [tex]\alpha[/tex] at a degree of freedom of  [tex]df =  34[/tex] is  

     [tex]X^2_{\alpha, 34 } =56.060[/tex]

From the value obtained we see that the test statistics does not lie within the region of rejection (1.e 56.060 , [tex]\infty [/tex]   )

Then

The decision rule is  

   Fail to reject the null hypothesis

The conclusion is  

   There is no sufficient evidence to accept  the manufacturing company claims

Other Questions