Final answer:
The most appropriate measures of center and spread for the daily high temperature data represented in a stem-and-leaf plot are the median and interquartile range, because they minimize the effect of potential outliers and non-symmetrical distributions in the data.
Step-by-step explanation:
The question asks which measures of center and spread are most appropriate for a set of data showing the daily high temperature in a town on April 1st for twenty-four random years. Since we are working with a stem-and-leaf plot, the data has already been organized to some extent, which helps in deciding the most suitable measures. Typically, the best measure of center would be the median, as it is not affected by outliers or extreme values that could affect the mean. A related measure of spread would be the interquartile range (IQR), which tells us the range within which the middle 50% of the data falls, also minimizing the impact of outliers.
Median and interquartile range are likely the most appropriate measures for this data since they deal well with potential outliers and non-symmetrical distributions that can occur in real-world data like temperatures. Although the mean and standard deviation are commonly used, they may not best represent the central tendency or spread of a data set if it includes outliers or is not symmetrical. The mode and range could give insight into the most frequent temperatures and the overall spread, but these measures don't give as nuanced a description of the data as the median and IQR do.