Answer:
Null hypothesis:[tex]p=0.72[/tex]
Alternative hypothesis:[tex]p \neq 0.72[/tex]
[tex] p_v = 2*P(|z|>z_{calc})[/tex]
And the best answer for this case is:
C. p-value
Step-by-step explanation:
Data given and notation
n represent the random sample taken
[tex]\hat p[/tex] estimated proportion of interest
[tex]p_o=0.72[/tex] is the value that we want to test
[tex]\alpha=0.05[/tex] represent the significance level
z would represent the statistic (variable of interest)
[tex]p_v[/tex] represent the p value (variable of interest)
Concepts and formulas to use
We need to conduct a hypothesis in order to test the claim that the true proportion i 0.72 or no.:
Null hypothesis:[tex]p=0.72[/tex]
Alternative hypothesis:[tex]p \neq 0.72[/tex]
When we conduct a proportion test we need to use the z statistic, and the is given by:
[tex]z=\frac{\hat p -p_o}{\sqrt{\frac{p_o (1-p_o)}{n}}}[/tex] (1)
The One-Sample Proportion Test is used to assess whether a population proportion [tex]\hat p[/tex] is significantly different from a hypothesized value [tex]p_o[/tex].
For this case the only probability that can be calculated from the statistic calculated is the p value given by:
[tex] p_v = 2*P(|z|>z_{calc})[/tex]
And the best answer for this case is:
C. p-value
