Answer:
[tex]a. \ H_o:p=0.45, \ \ \ \ H_a:p\neq 0.45\\\\b.\ \hat p=0.2209\\\\c. \ Yes\ (-4.2706<-1.96)[/tex]
Step-by-step explanation:
a. The professor's claim is that 45% first-timers fail his test. The null hypothesis is therefore stated as:
[tex]H_o:p=0.45[/tex]
-The alternative hypothesis is that more or less people fail the test as opposed to the professor's exact claim, hence:
[tex]H_a:p\neq 0.45[/tex]
b. To compute the P-value we use the z-value for a 95% confidence level:
[tex]z_{\alpha/2}=z_{0.025}=1.96[/tex]
#The proportion of failures in the sample of 86 is 19:
[tex]\hat p=\frac{19}{86}\\\\=0.2209[/tex]
The z-value is calculated as:
[tex]z=\frac{\hat p-p_o}{\sqrt{\frac{p_o(1-p_o)}{n}}}[/tex]
[tex]=\frac{0.2209-0.45}{\sqrt{\frac{0.45(1-0.45)}{86}}}\\\\\\=-4.2706[/tex]
-4.2706 is less than the stated confidence level for the given 45% proportion and greatly differs from it.
- Reject the null hypothesis as there is enough evidence to reject the claim.
-Hence,Yes, Professor Brown can conclude that percentage of failures differs from 45%.