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In R, we can run a t-test to determine if the temperatures provided come from a population with a mean of 98.6 degrees. we can calculate the 95% confidence interval of the estimate of the population mean.
To run a t-test in R, we can use the "t.test()" function. In this case, the temperatures are stored in the "temps" vector. We can perform the t-test with the following code:
```R
temps <- c(98.3, 97.9, 98.9, 99.1, 100.5, 99.8, 98.8, 99.5, 98.0, 97.7)
t.test(temps, mu = 98.6)
```
Running this code will provide the t-test results, including the t-statistic, degrees of freedom, and the p-value. From these results, we can determine if the temperatures come from a population with a mean of 98.6 degrees. If the p-value is below a chosen significance level (e.g., 0.05), we can reject the null hypothesis and conclude that the temperatures differ significantly from the given mean.
To calculate the 95% confidence interval of the estimate of the population mean, we can extract the confidence interval from the t-test results. The confidence interval will provide a range within which we can be 95% confident that the true population mean lies. The correct confidence interval will depend on the specific t-test results and cannot be determined without running the test. Therefore, among the provided options, none of them can be definitively chosen as the correct 95% confidence interval without the actual t-test results.
Learn more about confidence interval visit:
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