Answer:
The calculated z = 2.85 falls in the critical region z > 1.96 so we accept the null hypothesis that there is no difference between the population proportions for the two years.
Step-by-step explanation:
Let p1 be the sample of 1000 adults chosen in 2012 and
p2 be the sample of 1100 adults chosen in 2010
<u>Part a:</u>
The hypothesis that can be used to test for a significant difference between the population proportions for the two years is:
H0: p1-p2= 0 against the claim Ha: p1-p2≠0
<u>Part b:</u>
The sample proportion indicating that their financial security was more that fair in 2012 is
p1^= 410/1000= 0.41
In 2010 is:
p2^= 385/1100= 0.35
<u>Part c:</u>
p^c= 410+385/1000+1100= 0.3785
q^c= 1-p^c= 1-0.3785= 0.6124
The critical region is z > ±1.96
The test statistic is
z= p1^- p2^ / sqrt ( p^cq^c( 1/n1+ 1/n2)
z= 0.41-0.35 /sqrt( 0.3785*0.6124(1/1000 +1/1100)
z= 0.06 / 0.021036
z= 2.85
Conclusion
The calculated z = 2.85 falls in the critical region z > 1.96 so we accept the null hypothesis that there is no difference between the population proportions for the two years.
P- value : 0.00466
The result is significant( accept the null hypothesis) for value less than 0.05
<u>Part d:</u>
2012 2010
Sample 1000 1100
Proportions 0.41 0.35
Standard Error √0.41( 0.59)/1000 √0.35( 0.65)/1100
= 0.0155 0.01438
Standard Error for the difference = √0.0155² + 0.01438² =0.0211
p1-p2 ± z* standard error for the difference
0.41-0.35 ± 1.96 *( 0.0211)
0.06 ± 0.041356
-0.018644, 0.101356
The 95 % confidence interval estimate is (-0.018644, 0.10135
