You are a biomedical design engineer working on a new drug delivery pump. The pump is designed so that the minimum rate of delivery is not below $5 \mathrm{cc] /$ hour. A selected random sample of $n=9$ of the bottles have a sample average of $\bar[x]=5.02 \mathrm{cc) /$ hour and a sample variance of $0.0009(\mathrm{cc} / \text { hour })^{2}$. Use significance level $\alpha=0.01$. We would like to find if the drug delivery rate does not drop below the specifications. 06. The null hypothesis and the alternative hypothesis, respectively, are as follows: A. $H_{0}: \sigma [2)=0.0009\left(\fraccc}{\text { hour }} ight)^{2}$, and $H_(1): \sigma [2] eq 0.0909\left(\frac{cc}{\text hour }} ight)^{2}$ B. $H_{0}: \mu=5 \mathrm{cc) /$ hour, and $H_{1}: \mu eg 5 \mathrm{cc} /$ hour c. $H_CO]: \mu=5 \mathrm{cc} /$ hour, and $H_(1): mu>5 \mathrm{cc} /$ hour D. $H_(0): \mu=5 \mathrm{cc) /$ hour, and $H_(1): \mu0.03$ 07. To test the hypothesis, we must use the following test statistic: A. $z_{0}=\frac{\bar(x}-\mu_{0}}a / \sqrt{n}}$ B. $z_(0)=\frac{x-n p_10]}{\sqrt in p_cel\left(1-p_{0} ight)}}$ D. $x_{0}^{2}=\fract(n-1) 5^{2}}{\sigma_{0}^{2}}$ E. $t_0=\frac{\bar{x}-H_C0}}{5 / \sqrt{\pi}}$ SP.SD.0081