Assignment 01
Mahfuza Binte Mannan Tinni
2021-1-95-033
Difference between metric data and non-metric data
Metric Data: It is any reading which is at least at an interval scale. Interval scale and ratio
scale are metric data.
Ration Scale: it is the term we use where there is a real “Zero”, which means total absence of
whatever is being measured. It has a absolute zero. A persons zero income means no income
at all. The equation is: y=bx
Interval Scale: it describes a scale where the units of the scale measure a consistent concept. In
an interval scale the gap between 2 and 4 is the same as the gap between6 and 8. However, an
interval scale does not have a real zero. It is just a relative zero. The equation for interval scale
is: y=a+bx
Non-Metric Data: it refers to all the structured data market researchers use that is not metric.
Non-metric data refers information that is ranked which is called ordinal data. And information
that has no linear pattern to it which is called nominal or categorical data.
Nominal Scale: it is a measurement scale in which numbers serve as “tags” or “labels” to
identify or classify an object. A nominal scale does not depend on numbers because it deals
with non-metric attributes. This measurement deals with quantitative variables where numbers
have no value. For example: 1=Mild, 2= Moderate, 3=severe. Here numbers are simply used
a tags which has no numeric value.
Ordinal scale: it refers the ranking and ordering of the data without actually establishing the
degree of variation between them. Example: 1= totally satisfied, 2= satisfied. 3=neutral,
4=Dissatisfied, 5=Totally Dissatisfied. It is the customers decision ranking chart of a product.
Metrics refers to those variables having attribute whereas non-metric refer to those have
presence or absence of a characteristic or property, they are mutually exclusive.
Example:
Metric: sales, cost, number of clients
Non-metric: Gender, nationality