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What is the meaning of measurement in research? What difference does it make whether we measure in terms of a nominal, ordinal, interval or ratio...

What is the meaning of measurement in research? What difference does it make whether we measure in terms of a nominal, ordinal, interval or ratio scale? Explain giving examples

Answers

gregory
Measurement
Use of a yardstick to determine or judge some features of a physical or abstract objects or concepts ( eg. weight, height ,success, motivation ,etc)
Process of assigning numbers to objects or observations, the level of measurement being a function of the rules under which the numbers are assigned.
Process of mapping aspects of a domain onto other aspects of a range according to some rule of correspondence

Nominal Scale
Nominal scales are used for labelling variables, without any quantitative value.  Nominal scales could simply be called labels.
Cannot be quantified numerically but are either placed into sets or categories
Nominal scales provide convenient ways of keeping track of people, objects and events
There is no generally used measure of dispersion for nominal scales.
Chi-square test is the most common test of statistical significance that can be utilized, and for the measures of correlation, the contingency coefficient can be worked out.
Nominal scale is the least powerful level of measurement. It indicates no order or distance relationship and has no arithmetic origin. A nominal scale simply describes differences between things by assigning them to categories.
Example
Assign 0 if object (sex) is Male otherwise 1 for female
Assign the following on Marital Status
Single
Married
Widowed
Ordinal Scale
Data that cannot be quantified numerically but ranked in some way.
The greater than symbol (i.e., >) in connection with ordinal data may be used to designate happier than preferred to and so on.
comprises an ordering or ranking of values, although the intervals between the ranks are not intended to be equal
Ordinal scales are also used for questions that rate the quality of something (for example, very good, good, fair, and poor, etc.) and agreements (for example, Strongly agree, Agree, Disagree, etc.).

Example
How often have you felt like not coming to class? (Tick one)

Every day
Once a week
Sometimes
Never

Quantifiable data can be measured numerically, which means that it is more precise. Within the quantifiable classification there are two additional categories of interval and ratio data

Interval Scale
Numerical values are assigned along an interval scale with equal intervals, but there is no zero point where the trait being measured does not exist.
the difference between a score of 12 and 16 would be the same as the difference between a score of 40 and 42 hence, in contrast to ordinal data, the differences between categories are identical
Interval scales provide more powerful measurement than ordinal scales for interval scale also incorporates the concept of equality of interval. As such more powerful statistical measures can be used with interval scales. Mean is the appropriate measure of central tendency, while standard deviation is the most widely used measure of dispersion. Product moment correlation techniques are appropriate and the generally used tests for statistical significance are thet test and F test.

Ratio Scale
Ratio data are a subset of interval data, and the scale is again interval, but there is an absolute zero that represents some meaning,

Example, scores on an achievement test. If an employee undertakes a class -related test and scores zero, this would indicate a complete lack of knowledge or ability in this subject!
they tell us about the order, they tell us the exact value between units, AND they also have an absolute zerowhich allows for a wide range of both descriptive and inferential statistics to be applied
gregorymasila answered the question on December 13, 2017 at 12:27

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