- Data is information about something indicating a certain characteristic.
- Data can be classified into classified as below
- Generally Binary, Ordinal, and Nominal data are treated as Discrete data for analysis
Data Types
Quantitative data – Continuous Data
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Data which are measured using a Measuring instrument.
- Measurable (measurement scale or instrument)
- Endlessly Subdivided (in theory)
- Accuracy depends on the accuracy of the gauge
- Ratios of Continuous/Continuous or Continuous/Discrete or Discrete/Continuous are also treated as Continuous data
Quantitative data – Discrete Data
-
Only discrete or finite number of values that can
be only counted and can not be measured
- Countable (into Whole numbers)
- Can be categorized into a classification
- Cannot be broken down into smaller units
- Ratios of Discrete/Discrete is also Discrete data
Qualitative data – Binary Data
- Data with only two possible outcome
- Data can be represented as Numerical or Textural data as well
-
Example:
- Test Result – Pass/ Fail
- Plug Gauge result: Go/No-Go
- Bride/Groom: Passed/Rejected
Qualitative data – Nominal Data
- Data uses only the name variable instead of numerical value.
- The data does not have any order
-
Example:
- Directions – North, East, West& South
- Colors- Green,Red, Yellow, etc.
Qualitative data – Ordinal Data
- Qualitative Data with a set/ Natural order.
- Data does not have a standard
- Data can be measured in both Numerical & also Names
-
Example
- Grades – F, E, D, C, B, A
- Month- Jan, Feb,…,Dec
- Brightness:Light, Med& Dark
Quantitative data – Interval Data
- Includes all characteristics of ordinal scale but in addition, the distance between values is a constant size
- Interval scales are numeric scales in which we know both the order and the exact differences between the values.
- Example of an interval scale is Celsius temperature because the difference between each value is the same.
- The difference between 20 and 30 degrees is a measurable 10 degrees, as is the difference between 50 and 40 degrees.
Quantitative data – Ratio Data
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Highest Level of Measurement. Includes all
characteristics of interval level
- Distance between numbers are a known
- Constant size -
Major difference between
interval and ratio level
- Ratio level data has a meaningful zero point
- Ratio between the two numbers is meaningful - For Example: If the dial on the weighing scale shows zero,then there is a complete absence of weight
- If Mr. X earns INR 6Lakhs pa and Mr. Y earns 2 Lakhs pa, then Mr. X earns 3 times than Ravi