This document provides an overview of quantitative and qualitative research methods. It distinguishes between quantitative and qualitative research, describing how they differ in terms of data collection methods, sampling strategies, and analysis approaches. Quantitative research uses structured and closed-ended questioning, probability sampling, and statistical analysis to generalize to populations. Qualitative research employs semi-structured interviews, non-probability sampling, and inductive analysis to understand perspectives without generalization. Mixed methods combines quantitative and qualitative data collection and analysis to provide a comprehensive understanding of research problems.

1. Quantitative and Qualitative
Methods

2. Session
Contents
1. Overview of research methods
2. Distinction between quantitative
& qualitative research
3. Types & applicability of different
research methods
Session
Contents

3. Quantitative
vs. Qualitative
research

4. Differences between quantitative & qualitative research
The distinction between quantitative and qualitative research is not always as clear-cut:
 Individual and household surveys
o Commonly associated with quantitative, large sample research
o Could also be used for a qualitative case study
o Household surveys are questionnaires that are given to a sample of households in a population.
 Key Informant interviews and community discussions
o Commonly associated with qualitative, semi-structured data collection & analysis
o Could also be used for quantitative data collection & analysis where time and resources do not allow
a large, representative sample
o Key informants can be a wide range of people, including agency representatives, community
residents, community leaders, or local business owners.
o A community discussion is an online conversation between users and the specific spaces they
share to exchange ideas and words to participate, interact, share knowledge and communicate
about a common topic.
 Focus Group Discussions
o Perhaps the most distinctly qualitative research method, always administered using a semi-
structured data collection tool
o Often analysed using content analysis i.e. a somewhat quantitative approach counting the number
of times a theme or set of words appear with the discussion transcripts
o This content analysis can then inform the more in-depth qualitative analysis.
o A focus group is a small group of participants who share their feelings or perceptions on a
particular topic with researchers.
Differences between quantitative & qualitative research

5. Differences between quantitative & qualitative research
Distinction between the two can be made based on the following three criteria:
Quantitative Qualitative
1. Type of data collection Structured, close-ended data
(YES/NO) collection tools
Semi-structured (but not
unstructured) data collection tools
2. Type of analysis Measuring prevalence,
(randomly select sample)
quantifying issues (putting it in
numbers) , and primarily
involves deductive analysis
(logical approach)
Exploratory, and primarily involves
inductive analysis (primarily use
detailed readings of raw data)
3. Type of sampling strategy Can use both probability or
non-probability sampling 
generalisation to the wider
population possible
Non-probability sampling 
generalisation to the wider population
not possible

6. The term 'semi-structured qualitative study' (SSQS) –
is used here to refer to qualitative approaches, typically involving
interviews and observations, that have some explicit structure to them, in terms of
theory or method, but are not completely structured.
Structured data--
is information that is rigidly formatted so that it's easily searchable in a
relational database (Organized data) . It's usually quantitative information.
Examples include names, dates, emails, prices, and other information we're used to
seeing stored in spreadsheets

7. Types &
applicability of
different
research
methods

8. Types of research methods (1)
Category Type of research
methods
Description When to use this method
Quantitative Structured, probability
sampling/ census
Structured, close-ended data
collection;
Quantitative analysis;
Data collected from a census or
through large samples, with
sample size calculated based on
probability theory
To measure prevalence and make
generalizable claims,
To conduct deductive analysis
(relationship tests, verify hypothesis)
To identify key factors that influence a
particular outcome or understand the best
predictors of a specific outcome
Qualitative Structured, non-
probability sampling
Structured, close-ended data
collection;
Qualitative analysis;
Can be small or large sizes; non-
probability sampling
To measure prevalence (indicative only)
but contextual and/ or logistical
constraints do not allow for large,
representative samples
To draw indicative inferences from a
sample to a population

9. Types of research methods (2)
Category Type of research
methods
Description When to use this method
Qualitative Semi-structured, non-
probability sampling
Semi-structured data collection;
Qualitative analysis;
Relatively small sample sizes;
non-probability sampling
No measurement of prevalence or
verification of hypothesis needed;
No or limited prior understanding of the
situation to be studied and the specific
variables to be assessed;
To conduct inductive analysis i.e.
explore and develop a theory or pattern
of meaning, based on experiences,
observations and perspectives of the
situation being studied
Mixed
Methods
N/A Combines both qualitative and
quantitative methods, both in
terms of collecting and analyzing
both types of data but also using
both in tandem to enhance the
overall strength of the study
Quantitative or qualitative methods by
themselves inadequate to understand
the research problem;
To use all methods possible to obtain an
in-depth, comprehensive understanding
of the research problem.

10. The most powerful research method?
 Mixed methods research – if time, access, resources allow!
 Common misnomer that quantitative research is the strongest – not always!
 Not all issues need to explained in a quantifiable way
 Some issues are over-simplified if only explored in numeric terms
 In-depth explanation and contextualisation is useful
 Ultimately depends on the research objectives