What are the differences between nominal, ordinal, interval and ...

[B]

What are the differences between nominal, ordinal, interval and ratio data? Give examples.
 
  What will be an ideal response?

Question 2

From massive amounts of high-dimensional location data, algorithms that reduce the dimensionality of the data can be used to uncover trends, meaning, and relationships to eventually produce human-understandable representations.
 
  Indicate whether the statement is true or false

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Answer to Question 1

 Nominal data contain measurements of simple codes assigned to objects as labels, which are not measurements. For example, the variable marital status can be generally categorized as 1. single, 2. married, and 3 . divorced.
 Ordinal data contain codes assigned to objects or events as labels that also represent the rank order among them. For example, the variable credit score can be generally categorized as 1. low, 2. medium, or 3 . high. Similar ordered relationships can be seen in variables such as age group (i.e., child, young, middle-aged, elderly) and educational level (i.e., high school, college, graduate school).
 Interval data are variables that can be measured on interval scales. A common example of interval scale measurement is temperature on the Celsius scale. In this particular scale, the unit of measurement is 1/100 of the difference between the melting temperature and the boiling temperature of water in atmospheric pressure; that is, there is not an absolute zero value.
 Ratio data include measurement variables commonly found in the physical sciences and engineering. Mass, length, time, plane angle, energy, and electric charge are examples of physical measures that are ratio scales. Informally, the distinguishing feature of a ratio scale is the possession of a nonarbitrary zero value. For example, the Kelvin temperature scale has a nonarbitrary zero point of absolute zero.

Answer to Question 2

TRUE