This is a chapter from a book that discusses data related issues that are very crucial in the design and implementation of biometric systems.
Your task is to read the related sections and respond to the following questions:
Q1. Classify the following attributes as binary, discrete, or continuous. Also classify them as qualitative (nominal or ordinal) or quantitative (interval or ratio). Some cases may have more than one interpretation, so briefly indicate your reasoning if you think there may be some ambiguity.
(Example: Age in years -> Answer: Discrete, quantitative, ratio)
- Time in terms of AM or PM.
- Brightness as measured by a light meter.
- Brightness as measured by people’s judgments.
- Angles as measured in degrees between 0 and 360.
- Bronze, Silver, and Gold medals as awarded at the Olympics.
- Height above sea level.
- Number of patients in a hospital.
- ISBN numbers for books. (Look up the format on the Web.)
- Ability to pass light in terms of the following values: opaque, translucent, transparent.
- Military rank.
- Distance from the center of campus.
- Density of a substance in grams per cubic centimeter.
- Coat check number. (When you attend an event, you can often give your coat to someone who, in turn, gives you a number that you can use to claim your coat when you leave.)
Q2. The following attributes are measured for members of a herd of Asian elephants: weight, height, tusk length, trunk length, and ear area. Based on these measurements, what sort of similarity measure from Section 2.4 would you use to compare or group these elephants? Justify your answer and explain any special circumstances.
Q3. Explain why computing the proximity between two attributes is often simpler than computing the similarity between two objects.
Please do not look at instructor’s solutions, I know it is available online
Textbook chapter is attached