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Example of ordinal data

Ordinal data is characterized by ranks between the possible values.

If we take the example of the Richters scale, we can see that depending on the magnitude, the

heartquake can have the following values:

Richter

magnitudesDescription Earthquake effects

Less than 2.0 Micro Micro earthquakes, not felt.

2.0-2.9Minor

Generally not felt, but recorded.

3.0-3.9 Often felt, but rarely causes damage.

4.0-4.9 Light Noticeable shaking of indoor items, rattling noises. Significantdamage unlikely.

5.0-5.9 Moderate

Can cause major damage to poorly constructed buildings over

small regions. At most slight damage to well-designed

buildings.

6.0-6.9 StrongCan be destructive in areas up to about 160 kilometers (100 mi)

across in populated areas.

7.0-7.9 Major Can cause serious damage over larger areas.

8.0-8.9

Great

Can cause serious damage in areas several hundred miles

across.9.0-9.9 Devastating in areas several thousand miles across.

10.0+ Epic Never recorded; see below for equivalent seismic energy yield.

By the way, a heartquake of 5.5 magnitudes is more important than one of 3 but less than one 9. This

shows that there is an order between the data. In addition, if we have a look to the table below, we

can see that despite having the same interval of 0.5, the difference from one point to another in the

scale in Joule is not uniform. Therefore, this data is not of an interval type.

RichterApproximate Magnitude

Joule equivalent

0.0 63.1 kJ

0.5 355 kJ

1.0 2.00 MJ

1.5 11.2 MJ

2.0 63.1 MJ

2.5 355 MJ

3.0 2.00 GJ

3.5 11.2 GJ

Difference

of 9.2 MJ

Difference

of 51.9 MJ

Difference

of 0.5

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4.0 63.1 GJ

4.5 355 GJ

This is due to the fact that the Richter magnitude of an earthquake is determined from the logarithm

of the amplitude of waves recorded by seismographs. Because of the logarithmic basis of the scale,

each whole number increase in magnitude represents a tenfold increase in measured amplitude; in

terms of energy, each whole number increase corresponds to an increase of about 31.6 times the

amount of energy released, and each increase of 0.2 corresponds to a doubling of the energy

released.

Example of interval data

Interval data is characterized by a scale of measurement where the distance between any two

adjacent units of measurement (or 'intervals') is the same. The zero point is arbitrary and has not the

meaning ofnothing.

The time interval in months between 1.1. 2000 and 1.1.2001 is the same as that between 1.1.2009

and 1.1.2010. One could take as a reference period that one of 1.1.2000, which is considered as the

zero point in time. Of course, this does not mean that time does not exist in 1.1.2001.

http://en.wikipedia.org/wiki/Logarithmhttp://en.wikipedia.org/wiki/Amplitudehttp://en.wikipedia.org/wiki/Amplitudehttp://en.wikipedia.org/wiki/Logarithm