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It is given that $x_1=34$

$x_2=24$

$n_1=1679$

$n_2=1366$

Researchers want to know if there is a difference in the proportion of all Illinois high school freshmen and seniors who have used anabolic steroids or not.

Claim is difference between proportions.

The appropriate hypothesis:

Null: $H_0:p_1=p_2$

Alternative: $H_a:p_1鈮�p_2$

$p_1$is proportion of high school freshmen in Illinois that used anabolic steroids and $p_2$is proportion of high school seniors in Illinois that used anabolic steroids.

Sample proportion is role="math" localid="1654710840637" ${\hat{p}}_1=\frac{x_1}{n_1}=\frac{34}{1679}=0.02025$

and ${\hat{p}}_2=\frac{x_2}{n_2}=\frac{24}{1366}=0.01757$

$p_1鈮�p_2$ and proportion of high school freshmen in Illinois that used anabolic steroids is different from the proportion of high school seniors in Illinois that used anabolic steroids.

As ${\hat{p}}_1=0.02025$and ${\hat{p}}_2=0.01757$

and ${\hat{p}}_p=\frac{x_1+x_2}{n_1+n_2}=\frac{34+24}{1679+1366}=0.02836$

Value of test statistics is

$z=\frac{{\hat{p}}_1-{\hat{p}}_2-\left(p_1-p_2\right)}{\sqrt{{\hat{p}}_p\left(1-{\hat{p}}_p\right)}\sqrt{\frac{1}{n_1}+\frac{1}{n_2}}}$

role="math" localid="1654711122778" $=\frac{0.02025-0.01757-0}{\sqrt{0.02836(1-0.02836)}\sqrt{\frac{1}{1679}+\frac{1}{1366}}}鈮�0.44$

Probability is $P=P(Z<-0.44\text{or}Z>0.44)$

$=2P(Z<-0.44)$

$=2(0.3300)$

$=0.6600$

From given data and above calculations

$P>0.05鈬�\text{Fail to Reject}{H}_0$

There is no convincing evidence that the proportion of high school freshmen in Illinois that used anabolic steroids is different from the proportion of high school seniors in Illinois that used anabolic steroids.