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Module 2: Data Mining and Association Rule Mining

20212m

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 :

(i) Distance from center of campus
(ii) Ability to pass light in terms of opaque, translucent and transparent

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Attribute Classification

(i) Distance from center of campus

  • Type: Continuous (can take any real value, e.g., 0.5 km, 1.27 km).
  • Scale: Quantitative — Ratio (has a true zero — "0 distance" means literally at the campus center — and ratios are meaningful: 4 km is twice as far as 2 km).

(ii) Ability to pass light: opaque, translucent, transparent

  • Type: Discrete (a small, finite set of category values).
  • Scale: Qualitative — Ordinal. There is a natural order — opaque (passes no light) < translucent (passes some light) < transparent (passes most/all light) — but the "distance" between categories isn't numerically meaningful (we can't say translucent is exactly halfway between opaque and transparent in any measurable unit).

Ambiguity note

(ii) could arguably be seen as nominal if one ignores the light-passing order and treats the three labels as unordered categories, but since the attribute is explicitly defined by increasing "ability to pass light," the natural/expected interpretation is ordinal.

Attribute Discrete/Continuous Qualitative/Quantitative
Distance from campus center Continuous Quantitative — Ratio
Opaque/Translucent/Transparent Discrete Qualitative — Ordinal

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