Final answer:
The question about being 62 inches tall involves mathematical statistics related to data distribution, and using empirical data or z-scores can determine the commonality of that height in a population.
Step-by-step explanation:
Understanding Heights in Inches
When interpreting data about heights, such as the question about being 62 inches tall, we are typically dealing with mathematical statistics. One aspect of this is understanding data distribution and how it applies to real-world measurements, like height. In a given distribution of heights for a population, such as NBA players, the question of whether someone can be a certain height involves answering with respect to statistical likelihood based on measured samples.
To analyze the probability or frequency of a certain height, one might refer to empirical data or statistical tools like the empirical rule or z-scores. For example, if we know the mean and standard deviation of a group's heights, we could use a z-score to determine how common a particular height (like 62 inches) is within that group.
In some instances, statistical calculations can predict unrealistic heights. For example, the calculation Height = 79 + 3.5(3.89) = 90.67 inches, which suggests a height over 7.7 feet, indicates an extremely rare height among NBA players, thus deeming it unlikely. This type of analysis demonstrates how mathematical models can sometimes produce results that are not practical or representative of reality without considering the context of the data.