City Residents ( p 1 ) : n 1 = 50 , x 1 = 6 ; p ^ 1 = x 1 n 1 = 6 50 = 0.12 (p_1):n_1=50\ ,\ x_1=6\ \ ;
\ \hat p_1=\dfrac{x_1}{n_1}=\dfrac{6}{50}=0.12 ( p 1 β ) : n 1 β = 50 , x 1 β = 6 ; p ^ β 1 β = n 1 β x 1 β β = 50 6 β = 0.12
Suburban Residents ( p 2 ) : n 2 = 70 ; x 2 = 6 ; p ^ 2 = x 2 n 2 = 6 70 = 0.086 (p_2):n_2=70\ \ ;x_2=6\ \ ; \hat p_2=\dfrac{x_2}{n_2}=\dfrac{6}{70}=0.086 ( p 2 β ) : n 2 β = 70 ; x 2 β = 6 ; p ^ β 2 β = n 2 β x 2 β β = 70 6 β = 0.086
The 95% confidence level z Ξ± / 2 = 1.96 z_{\alpha/2}=1.96 z Ξ± /2 β = 1.96
Margin of error ( E ) = z Ξ± / 2 p ^ 1 ( 1 β p ^ 1 ) n 1 + p ^ 2 ( 1 β p ^ 2 ) n 2 (E)=z_{\alpha/2}\sqrt{\dfrac{\hat p_1(1-\hat p_1)}{n_1}+\dfrac{\hat p_2(1-\hat p_2)}{n_2}} ( E ) = z Ξ± /2 β n 1 β p ^ β 1 β ( 1 β p ^ β 1 β ) β + n 2 β p ^ β 2 β ( 1 β p ^ β 2 β ) β β
E = 1.96 β
0.12 Γ 0.88 50 + 0.086 Γ 0.914 70 = 1.96 Γ 0.0578 = 0.1133 E=1.96\cdot \sqrt{\dfrac{0.12\times 0.88}{50}+\dfrac{0.086\times 0.914}{70}}=1.96\times 0.0578=0.1133 E = 1.96 β
50 0.12 Γ 0.88 β + 70 0.086 Γ 0.914 β β = 1.96 Γ 0.0578 = 0.1133
Lower limit = ( p ^ 1 β p ^ 2 ) β E = ( 0.12 β 0.086 ) β 0.1133 = β 0.0793 (\hat p_1-\hat p_2)-E=(0.12-0.086)-0.1133=-0.0793 ( p ^ β 1 β β p ^ β 2 β ) β E = ( 0.12 β 0.086 ) β 0.1133 = β 0.0793
Upper limit = E β ( p ^ 2 β p ^ 1 ) = 0.1133 β ( 0.086 β 0.12 ) = 0.1473 E-(\hat p_2-\hat p_1)=0.1133-(0.086-0.12)=0.1473 E β ( p ^ β 2 β β p ^ β 1 β ) = 0.1133 β ( 0.086 β 0.12 ) = 0.1473
So, confidence interval = ( β 0.0793 , 0.1473 ) =(-0.0793,0.1473) = ( β 0.0793 , 0.1473 )
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