Scales of measurement in statistics

Jul 6, 20157 likes1,201 views

This document discusses the four scales of measurement used in statistics: nominal, ordinal, interval, and ratio. Nominal scales simply categorize variables without order, like gender or favorite color. Ordinal scales maintain unique identities and a rank order, but not necessarily equal distances, like the results of a horse race. Interval scales preserve equal distances between units in addition to identity and order, as in the Fahrenheit temperature scale. Ratio scales satisfy all properties by also having a true zero point, such as weight scales.

Subject: Statistics for Social Sciences
Presented: Mr. Shabbir Sahib
Presented by: Shahid Imran Khan Roll # 6
Scales of Measurement in Statistics
Statistical measurement scales are used to classify and enumerate various variables.
There are four measurement scales are used in Stats
1. Nominal
2. Ordinal
3. Interval
4. Ratio scales
Properties of Measurement Scales
These scales of measurement are used to one or more of the following properties.
1. Identity. Each value has a unique meaning.
2. Magnitude. Some values are larger and some are smaller.
3. Equal intervals. Scale units along the scale are equal to one another. This means,
for example, that the difference between 1 and 2 would be equal to the difference
between 9 and 10.
4. A minimum value of zero. The scale has a true zero point, below which no
values exist.
Nominal Scale
When measuring using a nominal scale, one simply names or categorizes responses.
Gender, handedness, favorite color, and religion are examples of variables measured on
a nominal scale. The essential point about nominal scales is that they do not suggest any
ordering among the responses. For example, when classifying people according to their
favorite color, there is no sense in which green is placed "ahead of" blue. Responses are
merely categorized. Nominal scales embody the lowest level of measurement.

Ordinal Scale
The ordinal scale has the property of both identity and magnitude. Each value on the
ordinal scale has a unique meaning, and it has an ordered relationship to every other
value on the scale.
An example of an ordinal scale in action would be the results of a horse race, reported
as "win", "place", and "show". We know the rank order in which horses finished the
race. The horse that won finished ahead of the horse that placed, and the horse that
placed finished ahead of the horse that showed. However, we cannot tell from this
ordinal scale whether it was a close race or whether the winning horse won by a mile.
Interval Scale
The interval scale of measurement has the properties of identity, magnitude, and equal
intervals.
A perfect example of an interval scale is the Fahrenheit scale to measure temperature.
The scale is made up of equal temperature units, so that the difference between 40 and
50 degrees Fahrenheit is equal to the difference between 50 and 60 degrees Fahrenheit.
With an interval scale, you know not only whether different values are bigger or
smaller, you also know how much bigger or smaller they are. For example, suppose it is
60 degrees Fahrenheit on Monday and 70 degrees on Tuesday. You know not only that
it was hotter on Tuesday, you also know that it was 10 degrees hotter.
Ratio Scale
The ratio scale of measurement satisfies all four of the properties of measurement:
identity, magnitude, equal intervals, and a minimum value of zero.
The weight of an object would be an example of a ratio scale. Each value on the weight
scale has a unique meaning, weights can be rank ordered, units along the weight scale
are equal to one another, and the scale has a minimum value of zero.
Weight scales have a minimum value of zero because objects at rest can be weightless,
but they cannot have negative weight.

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Scales of measurement in statistics

1. Subject: Statistics for Social Sciences Presented: Mr. Shabbir Sahib Presented by: Shahid Imran Khan Roll # 6 Scales of Measurement in Statistics Statistical measurement scales are used to classify and enumerate various variables. There are four measurement scales are used in Stats 1. Nominal 2. Ordinal 3. Interval 4. Ratio scales Properties of Measurement Scales These scales of measurement are used to one or more of the following properties. 1. Identity. Each value has a unique meaning. 2. Magnitude. Some values are larger and some are smaller. 3. Equal intervals. Scale units along the scale are equal to one another. This means, for example, that the difference between 1 and 2 would be equal to the difference between 9 and 10. 4. A minimum value of zero. The scale has a true zero point, below which no values exist. Nominal Scale When measuring using a nominal scale, one simply names or categorizes responses. Gender, handedness, favorite color, and religion are examples of variables measured on a nominal scale. The essential point about nominal scales is that they do not suggest any ordering among the responses. For example, when classifying people according to their favorite color, there is no sense in which green is placed "ahead of" blue. Responses are merely categorized. Nominal scales embody the lowest level of measurement.

2. Ordinal Scale The ordinal scale has the property of both identity and magnitude. Each value on the ordinal scale has a unique meaning, and it has an ordered relationship to every other value on the scale. An example of an ordinal scale in action would be the results of a horse race, reported as "win", "place", and "show". We know the rank order in which horses finished the race. The horse that won finished ahead of the horse that placed, and the horse that placed finished ahead of the horse that showed. However, we cannot tell from this ordinal scale whether it was a close race or whether the winning horse won by a mile. Interval Scale The interval scale of measurement has the properties of identity, magnitude, and equal intervals. A perfect example of an interval scale is the Fahrenheit scale to measure temperature. The scale is made up of equal temperature units, so that the difference between 40 and 50 degrees Fahrenheit is equal to the difference between 50 and 60 degrees Fahrenheit. With an interval scale, you know not only whether different values are bigger or smaller, you also know how much bigger or smaller they are. For example, suppose it is 60 degrees Fahrenheit on Monday and 70 degrees on Tuesday. You know not only that it was hotter on Tuesday, you also know that it was 10 degrees hotter. Ratio Scale The ratio scale of measurement satisfies all four of the properties of measurement: identity, magnitude, equal intervals, and a minimum value of zero. The weight of an object would be an example of a ratio scale. Each value on the weight scale has a unique meaning, weights can be rank ordered, units along the weight scale are equal to one another, and the scale has a minimum value of zero. Weight scales have a minimum value of zero because objects at rest can be weightless, but they cannot have negative weight.

Scales of measurement in statistics

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