It has long been stated that the mean temperature of humans is ${98.6}^{\circ }\mathrm{F}$. However, two researchers currently involved in the subject thought that the mean temperature of humans is less than ${98.6}^{\circ }\mathrm{F}$. They measured the temperatures of 111 healthy adults 1 to 4 times daily for 3 days, obtaining 500 measurements. The sample data resulted in a sample mean of ${98.5}^{\circ }\mathrm{F}$ and a sample standard deviation of ${0.8}^{\circ }\mathrm{F}$. Use the P-value approach to conduct a hypothesis test to judge whether the mean temperature of humans is less than ${98.6}^{\circ }\mathrm{F}$ at the $\alpha =0.01$ level of significance

Step 1 ：State the null hypothesis $H_0:\mu ={98.6}^{\circ }\mathrm{F}$ and the alternative hypothesis $H_a:\mu <{98.6}^{\circ }\mathrm{F}$

Step 2 ：Calculate the test statistic using the formula $t=\frac{\overline{x}-\mu }{s/\sqrt{n}}$ where $\overline{x}$ is the sample mean, $\mu$ is the hypothesized mean, $s$ is the sample standard deviation, and $n$ is the sample size

Step 3 ：Find the P-value associated with the calculated test statistic

Step 4 ：Compare the P-value to the significance level $\alpha =0.01$

Step 5 ：If the P-value is less than $\alpha$, reject the null hypothesis

Step 6 ：Since the P-value $0.0027$ is less than the significance level $\alpha =0.01$, we reject the null hypothesis

Step 7 ：Conclude that the mean temperature of humans is less than ${98.6}^{\circ }\mathrm{F}$

Step 8 ：The final answer is $\boxed{{\displaystyle \text{Reject }{H}_0}}$