Answer: [tex]H_0: p=0.30[/tex]
[tex]H_a: p <0.30[/tex]
Step-by-step explanation:
Definition:
Null Hypothesis : It is a statement about the population parameter that contains = , ≤ and ≥ signs.
Alternative hypothesis : It is also a statement about the population parameter against the null hypothesis that contains ≠ , < and > signs.
For the given situation.
Let [tex]\mu[/tex] be the population proportion of treated patients are uninsured.
A hospital director is told that 30% of the treated patients are uninsured.
Then, Null Hypothesis : [tex]H_0: p=0.30[/tex]
The director wants to test the claim that the percentage of uninsured patients is less than the expected percentage.
i.e. Alternative hypothesis : [tex]H_a: p <0.30[/tex]
Hence, the set of hypothesis :
[tex]H_0: p=0.30[/tex]
[tex]H_a: p <0.30[/tex]
