1. Measurement and Scaling
Techniques
VIKAS MINCHEKAR

2. Module 3. Measurement and Scaling Techniques
▪ 3.1 Measurement in Research and Measurement Scales
▪ 3.2 Sources of Error in Measurement
▪ 3.3 Tests of Sound Measurement
▪ 3.4 Technique of Developing Measurement Tools Scaling
▪ 3.5 Meaning of Scaling and Scale Classification Bases
▪ 3.6 Important Scaling Techniques and Scale Construction
Techniques

3. Sr.
No.
Subscale
No. of
Items
Cronbach’s
Alpha
Item
Retain
1 Personal Inadequacy (PI) 22 0.85 16
2 Interactions with Peers and Teachers (ITS) 20 0.80 17
3 Fear of Examination (FE) 16 0.84 11
4 Inadequate Facilities at College (IFC) 13 0.81 9
5 Parental Expectations and SES (PE & SES) 14 0.84 13
Total Item 85 --- 66

4. Sr. No. Subscales
I. Academic Abilities
I. Academic Interest
I. Study
I. Examination
I. Academic Interactions
I. Academic Efforts
I. Curriculum
I. Academic Future

5. Cognizance: Across the Different Corner of the
Globe

6. Cognizance: Across the Different Corner of the
Globe

7. Cognizance: Across the Different Corner of the
Globe

8. MEASUREMENT IN RESEARCH
▪ In our daily life we measure weight, height, or some other feature
of a physical object.
▪ We judge how well we like a song, a painting or the personalities
of our friends.
▪ Measurement is a relatively complex and demanding task,
especially when it concerns research.
▪ Definition
▪ The Measurement of Scale refers to the relationship between the
values assigned to objects and their attribute.

10. Nominal Scale
▪ Nominal scale is categorical data used to label variables without
any quantitative value. This data can only be categorized.
• Nominal scales are kind of like “names” or labels.
• This data has no order.
• You cannot perform arithmetic (+, – , *, / ) or logical operations
(<,>,=) on the nominal data.
What’s your name?
What is your qualification?
What is your experience?
Example
While filling out the survey you
see questions like

11. Ordinal Scale
▪ Ordinal data is also categorical data which is placed into some kind of
order by their position on the scale. This data can be ranked.
▪ With ordinal scales, the order of the values is important and significant,
but the differences between each one are not really known.
▪ Likert-type scales such as on a scale of 1 to 5, with one being strongly
disagreed and five being Strongly agreed represent ordinal data.
▪ Example
▪ A survey may ask how satisfied a customer
on 5 points Likert scale from
Strongly satisfied to Strongly dissatisfied

12. Ordinal Scale
▪ The difference between dissatisfied and very dissatisfied is not
perceived to be the same as the difference between very satisfied
and satisfied.
▪ ordinal scale is superior to nominal scale – the order is important,
as is the naming of the outcomes.

13. Interval Scale
▪ An interval scale is a way to measure data using numbers that
represent equal intervals on a scale. This means that the numbers
can be used to indicate the order of magnitude, but they cannot be
used to determine the exact amount.
▪ The main advantage of using an interval level of measurement is
that it allows for more precise comparisons than other types of
measurements. For instance, if you were measuring the height of
two people, you could use an interval level of measurement to say
that one person is exactly twice as tall as the other.
▪ temperature (Fahrenheit), temperature (Celcius), credit score (300-
850).

14. Ratio Scale
▪ A ratio is a level of measurement that is used to describe the
relationship between two or more things. It is often used to
compare quantities, such as size, speed, weight, or height.
Ratios can be written as fractions or decimals.
▪ With ratio level measurements, you can always be confident that
your units are accurate and consistent. That’s why ratio level
measurements are important in fields like science and
engineering.
▪ If you need to make precise measurements, then ratio level is
the way to go. It’s the most exact and reliable level of
measurement available. So if accuracy is key, make sure you’re
using a ratio scale.

15. Ratio Scale
A ratio scale is used to calculate the following.
•market share
•annual sales
•the price of an upcoming product
•number of consumers
Example
In the Kelvin temperature scale, for example, there are no negative degrees
of temperature – 0 indicating an absolute lack of thermal energy.
size, speed, weight, or height

16. Measurement Scales

17. Sources of Error in Measurement
▪ Respondents may be reluctant to express strong
negative feelings. Fatigue, boredom, anxiety, etc.
may limit the ability of the respondent
▪ Situational factors may also come in the way of
correct measurement.
▪ The interviewer’s behaviour, style and looks may
encourage or discourage certain replies from
respondents.
▪ Error may arise because of the defective measuring
instrument. The use of complex words, beyond the
comprehension of the respondent, ambiguous
meanings, poor printing, inadequate space for
replies, response choice omissions, etc. are a few
things that make the measuring instrument
defective and may result in measurement errors.
Error 3 & 4
Measurer Instrument
Error 2
Situation परिस्थिती
Error 1
Respondent प्रयुक्त

18. Tests of Sound Measurement
▪ Sound measurement must meet the tests of validity, reliability and
practicality.
▪ Validity refers to the extent to which a test measures what we
actually wish to measure.
▪ Reliability has to do with the accuracy and precision of a
measurement procedure.
▪ Practicality is concerned with a wide range of factors of economy,
convenience, and interpretability.

19. 1. Test of Validity
▪ (i) Content validity is the extent to which a measuring instrument provides adequate
coverage of the topic under study. If the instrument contains a representative sample of
the universe, the content validity is good. It can also be determined by using a panel of
persons who shall judge how well the measuring instrument meets the standards, but
there is no numerical way to express it.
▪ (ii) Criterion-related validity relates to our ability to predict some outcome or estimate
the existence of some current condition. Criterion-related validity is expressed as the
coefficient of correlation between test scores and some measure of future performance.
▪ (iii) Construct validity measure is said to possess construct validity to the degree that it
confirms to predicted correlations with other theoretical propositions. For determining
construct validity, we associate a set of other propositions with the results received from
using our measurement instrument. If measurements on our devised scale correlate in a
predicted way with these other propositions, we can conclude that there is some
construct validity.

20. 2. Test of Reliability
▪ A measuring instrument is reliable if it provides consistent results. A reliable measuring instrument
does contribute to validity, but a reliable instrument need not be a valid instrument. For instance, a
scale that consistently overweighs objects by five kgs., is a reliable scale, but it does not give a valid
measure of weight. But the other way is not true i.e., a valid instrument is always reliable. Accordingly,
reliability is not as valuable as validity, but it is easier to assess reliability in comparison to validity.
boredom, fatigue, etc., are minimised to the extent possible.
▪ Two aspects of reliability viz., stability and equivalence deserve special mention.
▪ The stability aspect is concerned with securing consistent results with repeated measurements of the
same person and with the same instrument.
▪ The equivalence aspect considers how much error may get introduced by different investigators or
different samples of the items being studied. by using trained and motivated persons to conduct the
research and also by broadening the sample of items used. This will improve the equivalence aspect.

21. 3. Test of Practicality
▪ The practicality characteristic of a measuring instrument can be judged in terms of
economy, convenience and interpretability.
▪ Economy consideration suggests that some trade-off is needed between the ideal
research project and that which the budget can afford.
▪ Convenience test suggests that the measuring instrument should be easy to
administer. For instance, a questionnaire, with clear instructions (illustrated by
examples), is certainly more effective and easier to complete than one which lacks
these features.
▪ Interpretability consideration is especially important when persons other than the
designers of the test are to interpret the results.

22. TECHNIQUE OF
DEVELOPING
MEASUREMENT TOOLS
TO BE CONTINUED IN THE NEXT LECTURE……..