Lecture - 07
Data collection
Data collection is the process of gathering and measuring
information on targeted variables in an established system, which enables one
to answer relevant questions and evaluate outcomes. The concept of data
collection is fundamental to research, business intelligence, and
decision-making processes across various fields.
Data collection is a critical phase in research, as even the
most well-designed study cannot succeed without the necessary data. It is a
challenging process that requires careful planning, dedication, patience, and
persistence to ensure successful completion. The process begins by identifying
the type of data needed, followed by selecting a sample from a specific
population. Once the sample is determined, an appropriate data collection
instrument is used to gather the required information from the chosen participants.
Data can be categorized into various types based on its
nature, source etc. Here are the main types of data:
1. Based on Nature:
- Qualitative
Data:
Non-numerical data that describes
qualities, characteristics, or attributes. It is often subjective and used to
understand concepts, opinions, or experiences.
- Examples:
Interview transcripts, open-ended survey responses, observations, or case
studies etc.
- Quantitative
Data:
Numerical data that can be measured
and analyzed statistically. It is objective and used to quantify variables.
- Examples:
Height, weight, age, sales figures, or test scores etc.
2. Based on Source:
- Primary
Data:
Data collected firsthand for a
specific research purpose. It is original and tailored to the study's needs.
- Examples:
Surveys, experiments, interviews, or observations etc.
- Secondary
Data:
Data that has already been
collected by someone else for a different purpose but is reused for new
research.
- Examples:
Government reports, academic journals, or historical records etc.
Primary Data collection
Primary data collection involves gathering original data
directly from sources for specific research purposes. It is crucial for
academic studies as it provides firsthand information tailored to the research
objectives. Below are the main primary data collection methods:
1. Surveys/Questionnaires
- A
structured set of questions designed to collect data from respondents.
- Cost-effective,
easy to administer, and scalable.
- Risk
of low response rates and biased answers.
2. Interviews
- A
direct, face-to-face or virtual conversation to gather detailed
information.
- Structured
(fixed questions), semi-structured (flexible), or unstructured
(open-ended).
- In-depth
insights and flexibility to explore topics.
- Time-consuming
and subject to interviewer bias.
3. Observations
- Systematically
watching and recording behaviors or events in their natural setting.
- Participant
(researcher is involved) or non-participant (researcher observes from a
distance).
- Provides
real-time, unbiased data.
- Observer
bias and time-intensive.
4. Experiments
- Manipulating
variables to observe their effect on outcomes in a controlled environment.
- Steps:
1.
Formulate Hypothesis: State the expected
relationship between variables.
2.
Design Experiment: Define control and
experimental groups.
3.
Conduct Experiment: Apply treatments and measure
outcomes.
4.
Analyze Results: Use statistical methods to test
the hypothesis.
5. Focus Groups
- A
group discussion led by a moderator to explore opinions on a specific
topic.
- Steps:
1.
Define Topic: Identify the research focus.
2.
Recruit Participants: Select a diverse group of
6-10 individuals.
3.
Moderate Discussion: Facilitate the conversation
using a guide and Controlling Time Without Being Obtrusive.
4.
Record Data: Take notes or record the session.
5.
Analyze Data: Identify common themes and
insights.
- Generates
rich, qualitative data and diverse perspectives.
- Dominant
participants may influence results.
6. Case Studies
- In-depth
analysis of a single case or a small number of cases.
- Provides
comprehensive understanding.
- Limited
generalizability and time-consuming.
Secondary data collection
Secondary data collection involves gathering information
that has already been collected and analyzed by others. This data is often used
for academic research, as it is cost-effective, time-saving, and provides
access to a wide range of information. Below is a brief explanation of
secondary data collection methods:
Published Sources
Published sources include books, academic journals,
newspapers, magazines, government reports, and industry publications. These
sources are widely available and often provide reliable and well-researched
information.
·
Use libraries, online catalogs, or academic
databases to find books, journals, or reports related to your topic.
Unpublished Sources
Unpublished sources include internal organizational reports,
theses, dissertations, and personal records. These sources often contain raw
data or detailed insights that are not publicly available.
·
Access university libraries or institutional
repositories for theses and dissertations. For internal reports, seek
permission from organizations.
Digital Sources
Digital sources include online databases, websites, blogs, newspaper
and social media platforms. These sources provide vast amounts of data, but
their credibility must be carefully evaluated.
·
Use trusted websites like government portals,
educational institutions, or reputable organizations (e.g., World Bank, WHO).
Archival Data
Archival data includes historical
records, census data, organizational archives, and historical documents. These
sources are useful for longitudinal studies or historical research.
·
Locate archives in libraries, museums, or
government institutions that house relevant historical records.
Assignment
For each data collection method, provide the following:
·
Description
with example
·
Procedure
·
Advantages
·
Disadvantages