This document discusses measurement and data presentation in research. It defines key terms like variables, attributes, and different types of variables. It also discusses scaling techniques used to assign numerical values to variables, including nominal, ordinal, interval, and ratio scales. Common scaling methods like Likert scales, Thurstone scales, Bogardus social distance scales, and Guttman scaling are explained. The document also covers classifying and tabulating data through coding, classification into categories and tables, and constructing frequency distributions. It concludes with providing a checklist for writing good research reports.

1. MODULE II
MEASUREMENT & DATA PRESENTATION

2. ATTRIBUTES AND VARIABLES
• Variable - a concept that varies
• Attributes are categories or levels of variable
• eg: gender-variable, male and female- attribute

3. of people, and the make of a car.
Figure 1.1 summarizes the different types of variables.
Figure 1.1 Types of variables.
Variable
Quantitative Qualitative or categorical
(e.g., make of a
computer, opinions of
people, gender)
Discrete
(e.g., number of
houses, cars,
accidents)
Continuous
(e.g., length,
age, height,
weight, time)

4. TYPES
• Based on cause-effect relationship
• Independent Variable & Dependent Variable
• The cause variable or the force or condition that acts on something
else is independent variable
• The variable that is the effect, result or outcome of another variable is
the dependent variable

5. • Intervening or mediating variable- in between independent and
dependent variable; show the link or mechanism between them
• Eg- Durkheim- suicide- married people-less suicide than single one.
Married one have more social integration. Major cause of one type of
suicide- lack of integration
• Here, 3 variable r/p- marital status (indep variable), causes the degree
of social integration (intervening variable) and which affects suicide
(dep variable)

6. SCALING TECHNIQUES
• In qntv res numbers are used to express qty; information about the world
in the form of numbers- do not naturally occur-researcher turn the data
into numbers
• Scaling- used in everyday language - how was your exam? How’s your
life? - we tend to judge movies, personalities etc
• We can measure both physical objects and abstract concepts
• The process of assigning number to objects or observation, according to a
set of rules

7. FOUR SCALES OF MEASUREMENT
• 1. Nominal - assign numbers to objects where different numbers indicate different objects ;
the numbers have no real meaning other than differentiating between objects (ex. 1.
Gender: 1 = transgender; 2 = female etc) (ex. 2 cricket players jersey)
• 2. Ordinal- assign numbers to objects (like nominal), but here the numbers also have
meaningful order (ex.1. place
fi
nished in a race 1st, 2nd, 3rd) (number indicates
placement , or order)
• 3. Interval - number have order (like ordinal), but there are also equal intervals between
adjacent categories (ex. Temperature in degrees of Fahrenheit) (no true zero - minus
degree is possible)
• 4. Ratio - differences are meaningful (like interval), plus ratios are meaningful and there is a
true zero point (eg. weight in Kg) (10 kg is twice as much as 5 kg) zero pounds means no
weight or an absence of weight (true zero point)

8. • Bogardus social distance scale, a device for measuring the varying degrees to which a
person would be willing to associate with a given class of people;
• Thurstone scaling, a technique that uses judges to determine the intensities of different
indicators; (sexism)
• Likert scaling, a measurement technique based on the use of standardized response
categories; and
• Guttman scaling, a method of discovering and using the empirical intensity structure
among several indicators of a given variable. Guttman scaling is probably the most popular
scaling technique in social research today (eg. women’s right to abortion; Woman’s health
is seriously endangered 89% Pregnant as a result of rape 81% Woman is not married 39% )
MOST COMMONLY USED SCALES

9. • Bogardus social distance scale
• Attitude related to different nationality
• Scale consists of items which denotes the extent of acceptance regarding a peculiar
nationality
• Assumption - people of one nationality keeps close relationship have less social distance
• Race, nation, community attitude is measured
• Reliability - high; .9, simple and practical
• Disadvantage - Statement not rationale, low validity, limited predictive validity
BOGARDUS SOCIAL DISTANCE SCALE

11. LIKERT SCALE
• Rensis Likert
• A multiple indicator or a multiple item measure of a set of attitudes relating to
a particular area
• To measure the intensity of feelings
• Comprises a series of statements known as items, focusing on a certain issue
• Each respondent is asked to to indicate his or her level of agreement (usually
a
fi
ve point scale from strongly agree to strongly disagree; seven points are
also there)

13. THURSTONE SCALE
• First formal technique to measure an attitude
• Developed by Louis Leon Thrustone in 1928, as a means of measuring
attitude towards religion
• Made up of statements about a particular issue and each statement has a
numerical value indicating how favourable or unfavourable it is judged to
be
• People check each of the statements to which they agree, and a mean
score is computed, indicating their attitude

15. • Louis Guttman
• Similar to Bogardus, based on the fact that some items under consideration may prove to be more-
extreme indicators of the variable than others
• They can be ranked in some order so that for a rational respondent, the response pattern can be
captured by a single index on that ordered scale (so that an individual who agrees with a particular
item also agrees with items of lower rank order)
• Unidimensional ; relevant item analysis; sexism example (Women should look after her child rather
than pursuing her career)
• high reliability -.85
• More useful in measuring political attitudes, social and economic attitudes
GUTTMAN SCALING

17. CLASSIFICATION TABULATION AND
INTERPRETATION
• CODING - computation purpose; a process of identifying and denoting a numeral to the
responses given by a respondent
• For classifying and recording the data from the tool on a spreadsheet
• Classi
fi
cation -a process of grouping data into different categories on the basis of certain
characteristics (classes, resemblance or differences in observation etc); usually into
attributes and variables ; to analyse the data. Here the data will be grouped into categories
and subcategories; removes unnecessary details to comprehend data; for ex. Class interval
• After classi
fi
cation, we present data into columns and rows - this process of summarising
data and presenting it in a compact form. By putting data into statistical table is called
tabulation

18. OBJECTIVES OF CLASSIFICATION AND
TABULATION
• Condensing the mass of data (so that similarities and differences can
be readily distinguished
• Most signi
fi
cant features of the data can be pin pointed at a glance
• Enables statistical treatment of the collected data (averages can be
computed, variations can be revealed, association can be studied,
forecasting, hypothesis formulation and testing)

19. PRINCIPLES OF CLASSIFICATION
• Lowest and highest value of the set of observations
• Knowledge of the data
• Utility of the class intervals for meaningful comparison and interpretation
• Classes should be collectively exhaustive and non-overlapping(mutually exclusive)
• The number of classes should not be too large other wise the summation of data will not be
served
• The number of classes would not be too small either (may affect distribution)
• Preferable equal width (for comparison) (Sturges rule for determining the number of classes K =
1+3.3 (log n) { K is the number of classes, n=no. of observation)

20. TYPES
• Exclusive (continuous) - when the class intervals are so
fi
xed that the
upper limit of one class is the lower limit of the next class and the
upper limit is not included in the class (eg. 1000-1100 [1000 but
under 1100)
• Inclusive (discontinuous) - when the upper and lower lift of one class
is included in the class itself (1000-1099; 1100-1199) {1000 but less
than or equal to 1099)

21. FREQUENCY DISTRIBUTION
• Discrete variables and continuous variables
• The manner in which the total number of observations are distributed
over different classes is called a frequency distribution

23. FREQUENCY DISTRIBUTION OF A DISCRETE
VARIABLE
• Data grouped into classes and the number of cases which fall in each
class are recorded
• Discrete vs continuous (ungrouped vs grouped frequency
distribution)

25. REPORT WRITING

26. CHECK LIST FOR A GOOD REPORT
TABLE 5 . 1
Abstract
Introduction - background, context, setting
Objectives and research questions
Literature review
Methods - overall strategy
- conceptual framework
- questionnaire
- sample
- data collection
- data analysis
Findings
Discussion
References
Appendices

27. 1. Abstract : brief summary; objectives, methods and
fi
ndings; 100 words or less, and is written last
2. Introduction : Introduce the topics; locate the study in its broader context and to describe its setting and
any necessary bac
k­
ground; from general to speci
fi
c
3. Literature Review : locate the present study in relation to the relevant literature and to show
4. Methods : Design, Strategy and Framework
5. Data Analysis: Results and Tables, presenting the data
6. Discussion and
fi
nding : concise, unambiguous interpretation of its meaning; it is a candid discussion of
what is in the Result section; organise the discussion according to hypotheses, discussing how the data is
related to the hypothesis
7. Conclusion - restate the research question and summarise
fi
ndings in the conclusion
8. References - Sources that were referred to in the text or notes of the report
9. Appendixes- contain additional information on methods of data collection (questionnaire or any tools) or
results (descriptive statistics)

28. REFERENCES
• Punch Keith F. 2003. Survey Research - The Basics. London: Sage.
• Newman Lawrence. 1994. Social Research Methods: Qualitative and
Quantitative Approaches. London: Allyn and Bacon
• Creswell, John W. 2009. Research Design: Qualitative, Quantitative,
and Mixed Methods Approaches. New Delhi: Sage
• Earl Babbie (2013). The Practice of Social Research, 13th Edn, New
Delhi: Cengage Learning