Respuesta :
Answer:
The sample size must be greater than 37 if we want to reject the null hypothesis.
Step-by-step explanation:
We are given that someone claims that the breaking strength of their climbing rope is 2,000 psi, with a standard deviation of 10 psi.
Also, we are given a level of significance of 5%.
Let [tex]\mu[/tex] = mean breaking strength of their climbing rope
SO, Null Hypothesis, [tex]H_0[/tex] : [tex]\mu[/tex] = 2,000 psi    {means that the mean breaking strength of their climbing rope is 2,000 psi}
Alternate Hypothesis, [tex]H_A[/tex] : [tex]\mu[/tex] < 2,000 psi    {means that the mean breaking strength of their climbing rope is lower than 2,000 psi}
Now, the test statistics that we will use here is One-sample z-test statistics as we know about population standard deviation;
             T.S.  =  [tex]\frac{\bar X-\mu}{\frac{\sigma}{\sqrt{n} } }[/tex]  ~ N(0,1)
where, [tex]\bar X[/tex] = ample mean strength = 1,997.2956 psi
      [tex]\sigma[/tex] = population standard devaition = 10 psi
      n = sample size
Now, at the 5% level of significance, the z table gives a critical value of -1.645 for the left-tailed test.
So, to reject our null hypothesis our test statistics must be less than -1.645 as only then we have sufficient evidence to reject our null hypothesis.
SO, Â T.S. < -1.645 Â {then reject null hypothesis}
     [tex]\frac{\bar X-\mu}{\frac{\sigma}{\sqrt{n} } } < -1.645[/tex]
     [tex]\frac{1,997.2956-2,000}{\frac{10}{\sqrt{n} } } < -1.645[/tex]
     [tex](\frac{1,997.2956-2,000}{10}) \times {\sqrt{n} } } < -1.645[/tex]
     [tex]-0.27044 \times \sqrt{n}< -1.645[/tex]
        [tex]\sqrt{n}> \frac{-1.645}{-0.27044}[/tex]
         [tex]\sqrt{n}>6.083[/tex]
         n > 36.99 ≈ 37.
SO, the sample size must be greater than 37 if we want to reject the null hypothesis.