Select three examples of data sets that do not have inherent zeros below. \( \square \) A. Temperature in degrees Fahrenheit \( \square \) B. A student's level of happiness measured from 0 to 10 \( \square \) C. Maximum wind speed during a hurricane \( \square \) D. Average monthly precipitation in inches \( \square \) E. Average IQ score of a high school class \( \square \) F. Number of years a college student was employed by a particular company

When it comes to data sets that lack inherent zeros, think about the context. For instance, temperatures in Fahrenheit can go below zero, but they don't represent an absence of temperature—just a different point on the scale! Similarly, a student's happiness level is subjective; a score of 0 doesn’t mean happiness is absent, but rather the lowest recorded value in their scale. For real-world applications, consider IQ scores as a common example in educational settings. While the average may be centered around 100, extreme scores closer to the theoretical minimum don't represent 'zero intelligence' but rather varying cognitive abilities. Likewise, a hurricane's maximum wind speed tells us how intense a storm can be, often yielding non-zero values even when the storm hasn’t yet formed.