Question #230727

There are 1000 students in the school of Engeering of 20,000 in the whole University of Zambia. In the study 200 students were found to be smokers in the school and 1000 in the whole university. Is there a statistical significant difference between the proportions of smokers in the school and the university


1
Expert's answer
2021-08-31T02:48:19-0400

Given


n1=1000,x1=200,p1^=0.2,n_1=1000, x_1=200, \hat{p_1}=0.2,


n2=20000,x2=1000,p2^=0.05.n_2=20000, x_2=1000, \hat{p_2}=0.05.

The value of the pooled proportion is computed as


pˉ=x1+x2n1+n2=200+10001000+20000=2350.0571\bar{p}=\dfrac{x_1+x_2}{n_1+n_2}=\dfrac{200+1000}{1000+20000}=\dfrac{2}{35}\approx0.0571

The following null and alternative hypotheses for the population proportion needs to be tested:

H0:p1=p2H_0: p_1=p_2

H1:p1p2H_1:p_1\not=p_2

This corresponds to a two-tailed test, and a z-test for two population proportions will be used.

Based on the information provided, the significance level is α=0.05,\alpha=0.05, and the critical value for a two-tailed test is zc=1.96.z_c=1.96.

The rejection region for this two-tailed test is R={z:z>1.96}.R=\{z:|z|>1.96\}.

The z-statistic is computed as follows:


z=p1^p2^pˉ(1pˉ)(1n1+1n2)z=\dfrac{\hat{p_1}-\hat{p_2}}{\sqrt{\bar{p}(1-\bar{p})(\dfrac{1}{n_1}+\dfrac{1}{n_2})}}

=0.20.05235(1235)(11000+120000)=\dfrac{0.2-0.05}{\sqrt{\dfrac{2}{35}(1-\dfrac{2}{35})(\dfrac{1}{1000}+\dfrac{1}{20000})}}


19.9431\approx19.9431

Since it is observed that z=19.9431>zc=1.96,|z|=19.9431>z_c=1.96, it is then concluded that the null hypothesis is rejected.

Using the P-value approach: The p-value is p=2P(Z>19.9431)0,p=2P(Z>19.9431)\approx0, and since p=0<0.05=α,p=0<0.05=\alpha, it is concluded that the null hypothesis is rejected.


Therefore, there is enough evidence to claim that the population proportion p1p_1 is different than p2,p_2, at the α=0.05\alpha=0.05 significance level.


Therefore there is a statistical significant difference between the proportions of smokers in the school and the university.



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