1.2 Data Classification

Question 1

Qualitative Data

Answer 1

Quality
- Consists of attributes, labels, or non numeric entries.

Question 2

Quantitative Data

Answer 2

Quantity
- Numerical measurements or counts.
EX Age, weight of a letter, temperature, height, cost.

Question 3

Nominal level of measurement

Answer 3

• Qualitative data only.
• Categorized using names, labels or qualities.
• No mathematical computations can be made.
  EX - SSN, Colors, Yes vs. No

Question 4

Qualitative Data

Answer 4

• Quality
• Consists of attributes, l

Question 14

Qualitative Data

Answer 14

Quality
- Consists of attributes, labels, or non numeric entries.
Ex Major, place of birth, eye color, zip code, ID number.

Question 15

Quantitative Data

Answer 15

Quantity
- Numerical measurements or counts.
Ex Ages, weight of a letter, temperature, height, cost.

Question 16

Nominal Level of Measurement

Answer 16

• Qualitative data only
• No mathematical computations can be made
• Categorized using names, labels or qualities
  Ex SSN, colors, yes vs. no

Question 17

Ordinal Level of Measurement

Answer 17

• Qualitative or Quantitative
• Differences between Data entries is NOT meaningful.
• Data can be arranged in order
  Ex rank top 5, course grades (A, B, C), types of cars

Question 18

Internal Level of Measurement

Answer 18

• Quantitative data
• Differences between Data entries is meaningful
• Data can be ordered
• Zero represents a position on a scale (not an inherent zero - zero does NOT imply “none”)
  Ex Temperature, years

Question 19

Ratio Level of Measurements

Answer 19

• Similar to interval level
• 200 entry is an inherent zero (implies “none”)
• A ratio of two data values can be formed
• One data value can be expressed as multiple of another
  Ex weights, prices, precipitation, distances, rainfall, money