Respuesta :
Answer:
[tex]z=\frac{0.286-0.250}{\sqrt{0.274(1-0.274)(\frac{1}{10500}+\frac{1}{5000})}}=4.696[/tex]
Step-by-step explanation:
1) Data given and notation
[tex]X_{US}=3000[/tex] represent the number of people reported that they owned the type of smart phone in question in U.S
[tex]X_{P}=1250[/tex] represent the number of people reported that they owned the type of smart phone in question in Poland
[tex]n_{US}=10500[/tex] sample of US selected
[tex]n_{P}=5000[/tex] sample of Poland selected
[tex]p_{US}=\frac{3000}{10500}=0.286[/tex] represent the proportion of people reported that they owned the type of smart phone in question in U.S
[tex]p_{P}=\frac{1250}{5000}=0.250[/tex] represent the proportion of people reported that they owned the type of smart phone in question in Poland
z would represent the statistic (variable of interest)
[tex]p_v[/tex] represent the value for the test (variable of interest)
[tex]\alpha=0.05[/tex] significance level given
2) Concepts and formulas to use
We need to conduct a hypothesis in order to check if is there is a difference in the two proportions analyzed, the system of hypothesis would be:
Null hypothesis:[tex]p_{US} - p_{P}=0[/tex]
Alternative hypothesis:[tex]p_{US} - p_{P} \neq 0[/tex]
We need to apply a z test to compare proportions, and the statistic is given by:
[tex]z=\frac{p_{US}-p_{P}}{\sqrt{\hat p (1-\hat p)(\frac{1}{n_{US}}+\frac{1}{n_{P}})}}[/tex] (1)
Where [tex]\hat p=\frac{X_{US}+X_{P}}{n_{US}+n_{P}}=\frac{3000+1250}{10500+5000}=0.274[/tex]
3) Calculate the statistic
Replacing in formula (1) the values obtained we got this:
[tex]z=\frac{0.286-0.250}{\sqrt{0.274(1-0.274)(\frac{1}{10500}+\frac{1}{5000})}}=4.696[/tex]
4) Statistical decision
Since is a two side test the p value would be:
[tex]p_v =2*P(Z>4.696)= 0.00000265[/tex]
Comparing the p value with the significance level assumed [tex]\alpha=0.05[/tex] we see that [tex]p_v<\alpha[/tex] so we can conclude that we have enough evidence to reject the null hypothesis, and we can say that we have significant differences in the two proportions analyzed.