Test the claim that the proportion of men who own cats is smaller than the proportion of women who own cats at the .10 significance level. Let p_M and p_F be the proportion of Men and Women who own cats respectively.
Based on a sample of 80 men, 40% owned cats
Based on a sample of 80 women, 51% owned cats
What is the test statistic and the critical value? Reject or Fail to Reject Null hypothesis?

Respuesta :

Answer:

 The  test statistics is [tex]t = -1.40[/tex]

  The critical value is  [tex]Z_{\alpha } = 2.33[/tex]

   The null hypothesis is rejected

Step-by-step explanation:

From the question we are told that

   The sample size  for men is  [tex]n_1 = 80[/tex]

    The sample  proportion of men that own a cat is  [tex]\r p _M = 0.40[/tex]

     The  sample  size for  women is [tex]n_2 = 80[/tex]

     The sample  proportion of women that own a cat is  [tex]\r p_F = 0.51[/tex]

     The level of significance is  [tex]\alpha = 0.10[/tex]

   The  null hypothesis is  [tex]H_o : \r p _M = \ r P_F[/tex]

    The alternative hypothesis is  [tex]H_a : \r p _M < \r p_F[/tex]

Generally the test statistic is mathematically represented as

        [tex]t = \frac{(\r p_M - \r p_F)}{\sqrt{\frac{(p_M*(1-p_M)}{n_1 } } + \frac{p_F*(1-pF)}{n_2 } }[/tex]

=>  [tex]t = \frac{(0.40 - 0.51)}{\sqrt{\frac{(0.40 *(1-0.41)}{80} } + \frac{0.51*(1-0.51)}{80 } }[/tex]

=>   [tex]t = -1.40[/tex]

The critical value of  [tex]\alpha[/tex]  from the normal distribution table is

     [tex]Z_{\alpha } = 2.33[/tex]

The p-value  is obtained from the z-table ,the value is  

    [tex]p-value = P( Z < -1.40) = 0.080757[/tex]

=>    [tex]p-value = 0.080757[/tex]

Given that the [tex]p-value < \alpha[/tex] then we reject the null hypothesis