Final answer:
To calculate upper and lower bounds in the context of confidence intervals, the highest and lowest values that the true parameter can be expected to fall within are computed using the point estimate and error bound. In the case of normal distribution regarding standard deviation, upper and lower bounds are the mean plus and minus one standard deviation, respectively.
Step-by-step explanation:
To calculate the upper bound and lower bound of a data set or confidence interval, there are various methods depending on the context. For a confidence interval, the upper bound is the highest value that the true parameter can be expected to fall within and the lower bound is the lowest value. Typically, these bounds are calculated using the point estimate plus or minus the error bound (EBM), which depends on the sample size and confidence level. Given a confidence interval, you can also find the sample mean by averaging the upper and lower bounds, or if you know the error bound, by subtracting the error bound from the upper value of the interval.
When considering a data set's dispersion, the upper and lower bounds might refer to the range, which would indeed be the maximum and minimum values. However, in terms of a normal distribution or when speaking about standard deviation, option C is correct: the upper bound would be the mean plus one standard deviation, and the lower bound would be the mean minus one standard deviation.
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