Respuesta :
Answer:
We want to test if the if p1 = the proportion of people who have myopia in 2019 is equal to p2 = proportion of people who have myopia in 2010 (alternative hypothesis) , then the system of hypothesis are:
Null hypothesis: [tex]p_1 = p_2[/tex]
Alternative hypothesis: [tex] p_1 = p_2[/tex]
And the best option would be:
b. H0:P1=P2; Ha：P1≠P2
Step-by-step explanation:
For this case we have the following info given:
[tex]X_1 = 228 [/tex] the myopia cases in 2019
[tex] n_1= 600[/tex] the sample size in 2019
[tex] \hat p_1= \frac{228}{600}= 0.38[/tex] estimated proportion of myopia cases in 2019
[tex]X_2 = 123 [/tex] the myopia cases in 2010
[tex] n_2= 400[/tex] the sample size in 2010
[tex] \hat p_2= \frac{123}{400}= 0.3075[/tex] estimated proportion of myopia cases in 2010
And we want to test if the if p1 = the proportion of people who have myopia in 2019 is equal to p2 = proportion of people who have myopia in 2010 (alternative hypothesis) , then the system of hypothesis are:
Null hypothesis: [tex]p_1 = p_2[/tex]
Alternative hypothesis: [tex] p_1 = p_2[/tex]
And the best option would be:
b. H0:P1=P2; Ha：P1≠P2
And we can conduct a two sample z proportion test in order to verify the hypothesis.
Answer:
- < 0.5 \leqslant pvalue < 0.10[/tex]
- answer C on khan academy
