Answer:
[tex]z=\frac{0.34 -0.3}{\sqrt{\frac{0.3(1-0.3)}{200}}}=1.23[/tex]
Now we can calculate the p value as:
[tex]p_v =2*P(z>1.23)=0.2187[/tex]
And the best conclusion would be:
a. H0: p = 0.3, HA: p ≠ 0.3, z = 1.23, p-value = 0.2187, so we conclude there is insufficient evidence for the politician’s claim and fail to reject the null hypothesis.
Step-by-step explanation:
Information given
n=200 represent the random sample taken
X=68 represent the number of families with computers
estimated proportion of families with computers
[tex]p_o=0.3[/tex] is the value to verify
z would represent the statistic
[tex]p_v[/tex] represent the p value
Hypothesis to test
We want to check if the true proportion is equal to 0.3 or not.:
Null hypothesis:[tex]p=0.3[/tex]
Alternative hypothesis:[tex]p \neq 0.3[/tex]
The statistic is given by:
[tex]z=\frac{\hat p -p_o}{\sqrt{\frac{p_o (1-p_o)}{n}}}[/tex] (1)
Replacing we got:
[tex]z=\frac{0.34 -0.3}{\sqrt{\frac{0.3(1-0.3)}{200}}}=1.23[/tex]
Now we can calculate the p value as:
[tex]p_v =2*P(z>1.23)=0.2187[/tex]
And the best conclusion would be:
a. H0: p = 0.3, HA: p ≠ 0.3, z = 1.23, p-value = 0.2187, so we conclude there is insufficient evidence for the politician’s claim and fail to reject the null hypothesis.