Use technology to find the P-value for the hypothesis test described below.
The claim is that for $12 \mathrm{AM}$ body temperatures, the mean is $\mu< 98.6^{\circ} \mathrm{F}$. The sample size is $n=6$ and the test statistic is $\mathrm{t}=-1.979$.
P-value $=\square($ Round to three decimal places as needed. $)$

Step 1 ：The claim is that for 12 AM body temperatures, the mean is less than 98.6°F. The sample size is 6 and the test statistic is -1.979.

Step 2 ：The P-value is the probability that a random chance generated the data, or something else that is equal or rarer, assuming that the null hypothesis is true.

Step 3 ：In this case, we are given the test statistic (t=-1.979) and the sample size (n=6). We can use the cumulative distribution function (CDF) of the t-distribution to find the P-value.

Step 4 ：The CDF gives the probability that a random variable is less than or equal to a certain value. Since our test statistic is negative and we are testing for a mean less than a certain value, we can use the CDF directly to find the P-value.

Step 5 ：Given that the sample size is 6, the degrees of freedom is 5 (n-1).

Step 6 ：Using the t-distribution table or a calculator, we find that the P-value is 0.052.

Step 7 ：Final Answer: The P-value for the hypothesis test is \(\boxed{0.052}\).