A confidence interval is a range of values that is likely to contain an unknown population parameter with a certain degree of confidence. In statistics, a confidence interval is computed at a designated confidence level, which is typically 95%, but other levels such as 90% or 99% can also be use. The confidence level represents the long-run proportion of confidence intervals (at the given confidence level) that theoretically contain the true value of the parameter. To calculate a confidence interval, we start with a point estimate of the population parameter, such as the sample mean or proportion, and then calculate the standard error of the estimate (ie. SEM). We then use a t-distribution to calculate the margin of error. The margin of error is the amount by which the point estimate may vary due to random sampling error. Finally, we construct the confidence interval by adding and subtracting the margin of error from the point estimate. Use the correct of data and show all calculations required to answer the following questions:
Construct a 95% confidence interval for the data subset A1 to A25.