Respuesta :
Answer:
a
The determination is
There is sufficient to conclude that proportion of the single policy
b
The 95% confidence interval is [tex] 0.0498 < p_1 - p_2 < 0.1302 [/tex]
holders is difference from the proportion of married policy holders
Step-by-step explanation:
From the question we are told that
The sample size for single policy holders is [tex]n_1 = 500[/tex]
The number of single police holders making claim is k = 95
The sample size for married policy holders [tex]n_2 = 800[/tex]
The number of double police holders making claim is u = 80
The level of significance is [tex]\alpha = 0.05[/tex]
Generally the critical value of [tex]\frac{\alpha }{2}[/tex] obtained from the
normal distribution table is
[tex]Z_{\frac{\alpha }{2} } = 1.96[/tex]
The null hypothesis is [tex]H_o : p_1 = p_2[/tex]
The alternative hypothesis is [tex]H_a : p_1 \ne p_2[/tex]
The sample proportion of single police holders making claim is
[tex]\r p_ 1 = \frac{k}{n_1}[/tex]
=> [tex]\r p_ 1 = \frac{95}{500}[/tex]
=> [tex]\r p_ 1 = 0.19[/tex]
The sample proportion of married police holders making claim is
[tex]\r p_ 2 = \frac{u}{n_2}[/tex]
=> [tex]\r p_ 2 = \frac{80}{800}[/tex]
=> [tex]\r p_ 2 = 0.1[/tex]
Generally the pooled sample proportion is mathematically represented as
[tex]\r p = \frac{k + u}{n_1 + n_2}[/tex]
=> [tex]\r p = \frac{95 + 80}{500 + 800}[/tex]
=> [tex]\r p = 0.1346 [/tex]
Generally the test statistics is mathematically represented as
[tex]z = \frac{\r p_1 - \r p_2 }{ \sqrt{ \r p (1 - \r p )* [\frac{1}{n_1} + \frac{1}{n_2} ]} }[/tex]
=> [tex]z = \frac{0.19 - 0.1 }{ \sqrt{0.1346 (1 - 0.1346 )* [\frac{1}{500} + \frac{1}{800} ]} }[/tex]
=>[tex]z = 4.6256 [/tex]
Generally the p-value is mathematically represented as
[tex]p-value = 2* P(Z >4.6256 )[/tex]
From the z table [tex]P(Z >4.6256 ) = 0 [/tex]
[tex]p-value = 2* 0 = 0[/tex]
From the calculation we see that the p-value < [tex]\alpha[/tex] so the null hypothesis is rejected
Hence there is sufficient to conclude that proportion of the single policy holders is difference from the proportion of married policy holders
Generally the standard error is mathematically represented as
[tex]SE = \sqrt{ \frac{\r p_1 (1 -\r p_1)}{n_1} + \frac{\r p_2 (1 -\r p_2)}{n_2} }[/tex]
=> [tex]SE = \sqrt{ \frac{0.19 (1 -0.19)}{500} + \frac{ 0.1 (1 - 0.1)}{800} }[/tex]
=> [tex]SE =0.0205012[/tex]
Generally the margin of error is mathematically represented as
[tex]E = Z_{\frac{\alpha }{2} } * SE[/tex]
=> [tex]E = 1.96 *0.0205012 [/tex]
=> [tex]E = 0.0402035[/tex]
Generally the 95% confidence level is mathematically represented as
[tex]\r p_1 - \r p_2 - E < p_1 - p_2 < \r p_1 - \r p_2 + E[/tex]
=> [tex]0.19 - 0.10 -0.0402035 < p_1 - p_2 < 0.19 - 0.10 + 0.0402035 [/tex]
=> [tex]0.09 -0.0402035 < p_1 - p_2 < 0.09 + 0.0402035 [/tex]
=> [tex] 0.0498 < p_1 - p_2 < 0.1302 [/tex]
