Answer:
[tex]z=\frac{0.60 -0.72}{\sqrt{\frac{0.72(1-0.72)}{80}}}=-2.39[/tex] Â
Step-by-step explanation:
Data given and notation
n=80 represent the random sample taken
[tex]\hat p=0.6[/tex] estimated proportion of interest
[tex]p_o=0.72[/tex] is the value that we want to test
[tex]\alpha[/tex] represent the significance level
z would represent the statistic (variable of interest)
[tex]p_v[/tex] represent the p value (variable of interest) Â
Concepts and formulas to use Â
We need to conduct a hypothesis in order to test the claim that the true proportion is equal to 0.72 or no.: Â
Null hypothesis:[tex]p=0.72[/tex] Â
Alternative hypothesis:[tex]p \neq 0.72[/tex] Â
When we conduct a proportion test we need to use the z statistic, and the is given by: Â
[tex]z=\frac{\hat p -p_o}{\sqrt{\frac{p_o (1-p_o)}{n}}}[/tex] (1) Â
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].
Calculate the statistic Â
Since we have all the info required we can replace in formula (1) like this: Â
[tex]z=\frac{0.60 -0.72}{\sqrt{\frac{0.72(1-0.72)}{80}}}=-2.39[/tex] Â