Levels of Measurement

Sarfraz Ahmad
Lecturer
KUST, Kohat

1. Levels of Measurement

2. Levels of Measurement Introduction :- The level of measurement refers to the relationship among the values that are assigned to the attributes for a variable. What does that mean? Begin with the idea of the variable, in this example "party affiliation."  That variable has a number of attributes.

3. Levels of Measurement Introduction :- Let's assume that in this particular election context the only relevant attributes are "republican", "democrat", and "independent ". For purposes of analyzing the results of this variable, we arbitrarily assign the values 1, 2 and 3 to the three attributes . The   level of measurement  describes the relationship among these three values.

4. Levels of Measurement Introduction :- In this case, we simply are using the numbers as shorter placeholders for the lengthier text terms. We don't assume that higher values mean "more" of something and lower numbers signify "less". We don't assume the value of 2 means that democrats are twice something that republicans are.

5. Levels of Measurement Introduction :- We don't assume that republicans are in first place or have the highest priority just because they have the value of 1. In this case, we only use the values as a shorter name for the attribute. Here , we would describe the level of measurement as "nominal ".

6. Levels of Measurement Why is Level of Measurement Important ? First , knowing the level of measurement helps you decide how to interpret the data from that variable . When you know that a measure is nominal (like the one just described), then you know that the numerical values are just short codes for the longer names .

7. Levels of Measurement Why is Level of Measurement Important ? Second , knowing the level of measurement helps you decide what statistical analysis is appropriate on the values that were assigned. If a measure is nominal, then you know that you would never average the data values or do a t-test on the data .

8. Levels of Measurement There are typically four levels of measurement that are defined: Nominal Ordinal Interval Ratio

9. Levels of Measurement

10. Levels of Measurement Incremental Progress Measure Property Mathematical Operators Advanced Operations Central Tendency Nominal Classification, Membership =, != Grouping Mode Ordinal Comparison, Level >, < Sorting Median Interval Difference, Affinity +, - Yardstick Mean, Deviation Ratio Magnitude, Amount *, / Ratio Geometric Mean, Coeff . of Variation

11. Levels of Measurement Nominal level The nominal type differentiates between items or subjects based only on their names or (meta-)categories and other qualitative classifications they belong to; thus dichotomous data involves the  construction of classifications  as well as the classification of items.

12. Levels of Measurement Examples of these classifications include gender, nationality, ethnicity, language, genre, style, biological species, and form.  In a university one could also use hall of affiliation as an example. Other concrete examples are in  grammar , the  parts of speech : noun, verb, preposition, article, pronoun, etc. in politics,  power projection : hard power, soft power, etc. in biology, the  taxonomic ranks  below domains: Archaea , Bacteria, and Eukarya in  software engineering , type of  faults : specification faults, design faults, and code faults

13. Levels of Measurement Ordinal scale The ordinal type allows for  rank order  (1st, 2nd, 3rd, etc.) by which data can be sorted, but still does not allow for relative  degree of difference  between them. Examples include, on one hand,  dichotomous  data with dichotomous (or dichotomized) values such as 'sick' vs. 'healthy' when measuring health , 'guilty ' vs. 'not-guilty' when making judgments in courts,

14. Levels of Measurement Ordinal scale 'wrong/false ' vs. 'right/true' when measuring  truth value , and, on the other hand,  N on-dichotomous  data consisting of a spectrum of values, such as 'completely agree', 'mostly agree', 'mostly disagree', 'completely disagree' when measuring  opinion .

15. Levels of Measurement Interval scale The interval type allows for the  degree of difference  between items, but not the ratio between them. Examples include  temperature  with the  Celsius scale , which has two defined points (the freezing and boiling point of water at specific conditions) and then separated into 100 intervals,   percentage  such as a percentage return on a  stock   location  in Cartesian coordinates, and  direction  measured in degrees from true or magnetic north.

16. Levels of Measurement Ratio scale The ratio type takes its name from the fact that measurement is the estimation of the ratio between a magnitude of a continuous quantity and a unit magnitude of the same kind ( Michell , 1997, 1999). A ratio scale possesses a meaningful (unique and non-arbitrary) zero value. Most measurement in the physical sciences and engineering is done on ratio scales.

17. Levels of Measurement Ratio scale Examples include  mass ,  length ,  duration ,  plane angle ,  energy  and  electric charge . In contrast to interval scales, ratios are now meaningful because having a non-arbitrary zero point makes it meaningful to say, for example, that one object has "twice the length" of another (= is "twice as long ").

18. Levels of Measurement Ratio scale Very informally, many ratio scales can be described as specifying "how much" of something (i.e. an amount or magnitude) or "how many" (a count). The   Kelvin  temperature scale is a ratio scale because it has a unique, non-arbitrary zero point called  absolute zero .

19. Thank You