Respuesta :
Answer:
Null hypothesis:[tex]p\leq 0.3[/tex]
Alternative hypothesis:[tex]p > 0.3[/tex]
Critical value: [tex] z_{\alpha/2}= 1.64[/tex]
Test statistic: [tex]z=\frac{0.462 -0.3}{\sqrt{\frac{0.3(1-0.3)}{65}}}=2.85[/tex]
For this case the calculated value is higher than the critical value so then we can reject the null hypothesis. And we can conclude that the true proportion of cars with emissions systems which failed to meet pollution control guidelines for this case is significantly higher than 0.30 or 30%
Step-by-step explanation:
Information given
n=65 represent the random sample taken
X=30 represent the number of cars with emissions systems which failed to meet pollution control guidelines
[tex]\hat p=\frac{30}{65}=0.462[/tex] estimated proportion of cars with emissions systems which failed to meet pollution control guidelines
[tex]p_o=0.30[/tex] is the value to verify
[tex]\alpha=0.05[/tex] represent the significance level
z would represent the statistic
[tex]p_v[/tex] represent the p value
Hypothesis to test
We want to verify if the true proportion for this case is higher than 0.3 or no, the system of hypothesis are:
Null hypothesis:[tex]p\leq 0.3[/tex]
Alternative hypothesis:[tex]p > 0.3[/tex]
The statistic for this case would be:
[tex]z=\frac{\hat p -p_o}{\sqrt{\frac{p_o (1-p_o)}{n}}}[/tex] (1)
Replacing the info we got:
[tex]z=\frac{0.462 -0.3}{\sqrt{\frac{0.3(1-0.3)}{65}}}=2.85[/tex]
The critical value for this case would be taking in count the significance level in the right tail:
[tex] z_{\alpha/2}= 1.64[/tex]
For this case the calculated value is higher than the critical value so then we can reject the null hypothesis. And we can conclude that the true proportion of cars with emissions systems which failed to meet pollution control guidelines for this case is significantly higher than 0.30 or 30%