This document discusses various methods for collecting data in research. It describes two main types of data - quantitative and qualitative. Quantitative data deals with numerical values while qualitative data involves non-numerical values like opinions. Some common data collection methods are surveys, interviews, focus groups, observations, experiments, case studies, and document analysis. Each method has strengths and weaknesses for collecting different types of information. Using multiple methods can provide a more comprehensive understanding of the topic being researched.

1. METHODS
OF DATA

2. METHODS OF DATA COLLECTION
INTRODUCTION :
Data collection methods are techniques used by
researchers to gather information and data from
various sources. These methods are used to
collect both quantitative and qualitative
data and can be applied in various fields such as
social sciences, education, business, healthcare,
and many others. The choice of method depends
on the research question, the nature of the data,
and the resources available to the researcher.

3. TYPES OF DATA
1.Quantitative data: This type of data deals with numerical
values, such as measurements, quantities, and counts. It is
typically analyzed using statistical methods to identify
patterns and relationships between variables. Examples of
quantitative data include height, weight, age, test scores, and
sales figures.
2.Qualitative data: This type of data deals with non-
numerical values, such as opinions, attitudes, feelings, and
behaviors. It is typically analyzed using thematic
analysis, content analysis, or discourse analysis to identify
themes and patterns in the data. Examples of qualitative data
include interviews, focus group discussions, open-ended
survey responses, and observations.

4. 4

5.  Surveys/questionnaires: Surveys
involve asking a set of standardized
questions to a
large number of participants.
Surveys can be conducted through
paper-based questionnaires or
online surveys.

6. Surveys and questionnaires can be used to
collect both qualitative and quantitative
data, depending on the type of questions
asked. They are useful for collecting data on
attitudes, beliefs, behaviors, and
demographics. Surveys and questionnaires
are relatively easy to administer and can be
used to collect data from a large number of
participants in a relatively short amount of
time.

7.  Interviews
Interviews involve face-to-face
or virtual conversations between the
researcher and the participant.
Interviews can be structured, semi-
structured, or unstructured,
depending on the level of
standardization required.

8. Here are some of the reasons why interviews are
important in collecting data:
In-depth exploration: Interviews allow researchers to explore
a topic in-depth and to ask follow-up questions to clarify or
expand upon a participant's response. This can provide a
more detailed understanding of the participant's perspective
and experiences.
Flexibility: Interviews can be structured, semi-structured, or
unstructured, depending on the level of standardization
required. This allows for greater flexibility in the type of data
collected, and can be adapted to the needs of individual
participants.

9. Participant perspective: Interviews allow participants to
express their own perspectives and experiences in their own
words, without being limited by pre-determined response
options or categories.
Rich qualitative data: Interviews can provide rich qualitative
data that can be used to develop theories or hypotheses
about a topic. This can help to provide a deeper
understanding of complex social phenomena.
Participant engagement: Interviews can be a more engaging
method of data collection for participants, as they have the
opportunity to actively participate in the research process
and share their experiences.

10.  Focus groups: Focus groups
involve a small group of
participants who discuss a
specific topic in-depth in a
group setting. Focus groups can
provide rich qualitative data and
insights into group dynamics.

11.  Observations: Observations
involve watching and recording
the behavior of individuals or
groups in a natural setting.
Observations can be structured
or unstructured and can provide
valuable data on social
interactions and behaviors.

12.  Experiments: Experiments
involve manipulating one or
more variables to observe the
effect on an outcome of interest.
Experiments can provide strong
evidence of causality but may be
difficult to implement in certain
settings.

13. experiments may be difficult to implement in
certain settings for the following reasons:
Ethical considerations
Cost and time
Control
Generalizability

14.  Case studies: Case studies
involve in-depth analysis of a
single individual, group, or
organization. Case studies
can provide rich qualitative
data and insights into
complex social phenomena.

15.  Document analysis: Document
analysis involves analyzing
written or recorded data such
as reports, meeting minutes,
or social media posts.
Document analysis can
provide insights into social
and educational policies and

16. For example, documents may not provide a
complete picture of social phenomena, as they
may be subject to bias or may not capture all
relevant information.
However, careful attention to the selection and
analysis of documents can help to ensure the
validity and
reliability of the data collected.
In many research studies, a combination of
document analysis and
other data collection methods is used to provide a
more comprehensive understanding of the

17. Overall, data collection methods are
important because they provide a
systematic and structured approach to
collecting data, which ensures that the
data collected is valid, reliable, and
relevant to the research question being
investigated. This, in turn, allows for
accurate conclusions to be drawn
and informed decisions to be made
based on the data collected.

18. Thank
you for
Listening
!

19. Prepared by: Shena L.
Cano