The question deals with calculating a specific percentile of women's heights and understanding the relationship between confidence intervals and statistical estimates. It involves statistical concepts such as z-scores, percentiles, and sample data interpretation.
The question presents a problem related to determining the height that demarcates the shortest 1% of women’s heights from the rest. This is a statistics problem involving the concept of percentiles and cumulative relative frequency. The specific task described requires knowledge of the empirical rule or the use of the standard normal distribution (z-scores) to identify a cutoff point. Such a problem would typically be solved by calculating the z-score corresponding to the 1st percentile and then using the mean and standard deviation of the distribution to find the actual height. The mention of a confidence interval would imply that the student is expected to learn the relationship between confidence levels and the accuracy of statistical estimates.
Examples given in the question suggest analyzing height data from a sample and interpreting percentages and intervals from the distribution of these heights. Based on the mention of Table 1.15 and Table 8.8, it appears that sample data sets are provided and certain statistical procedures such as drawing a sample, calculating mean, and constructing a confidence interval are expected to be performed.
The data regarding heights can be considered as continuous numerical data, which has infinite possible values within a given range. To gather such data in a way that is characteristic of all male semi-professional soccer players, a proper sampling method must be employed. This typically involves random sampling from the broader population to ensure representativeness, ultimately allowing for generalizable conclusions.