Name: Eden Quieta
BSEd-Filipino 3
Data Collection
Data collection refers to the systematic process of gathering information from
various sources to address a specific research question or problem. This process
is essential for generating meaningful insights and ensuring the validity and
reliability of research findings.
Types of Data
Data collected in research can be broadly categorized into two types:
1. Quantitative Data
Quantitative data are numerical and measurable. They focus on quantifiable
variables and are often analyzed using statistical methods.
Examples: Test scores, income levels, population counts, and temperature
readings.
2. Qualitative Data
Qualitative data are descriptive and non-numerical, capturing subjective
experiences, emotions, or cultural phenomena.
Examples: Interview transcripts, open-ended survey responses, and
observational notes.
Methods of Data Collection
Data collection methods can be broadly divided
into primary and secondary techniques.
Primary Data Collection Methods
Primary methods involve collecting data directly from the source.
a. Surveys and Questionnaires
Surveys are structured instruments designed to gather specific information from
participants.
Advantages: Cost-effective, scalable, and suitable for large populations.
Examples: Online surveys on consumer behavior, satisfaction questionnaires
in hospitals.
b. Interviews
Interviews involve direct, in-depth questioning of individuals to obtain detailed
insights.
Advantages: Flexible and allows exploration of complex topics.
Examples: Interviews with CEOs on leadership strategies, conversations
with patients about healthcare experiences.
c. Observation
This method involves watching and recording behaviors or events in their natural
settings.
Advantages: Provides contextual and real-time data.
Examples: Observing classroom dynamics, monitoring wildlife behaviors.
d. Experiments
Experiments involve controlled environments where variables are manipulated to
study cause-and-effect relationships.
Advantages: High reliability and precision.
Examples: Testing the effectiveness of a new drug, studying consumer
reactions to product packaging.
e. Focus Groups
Focus groups consist of small, guided discussions to explore participants’
opinions, attitudes, and perceptions.
Advantages: Rich qualitative insights and group dynamics.
Examples: Discussions on advertising strategies, community feedback on
policy changes.
Secondary Data Collection Methods
Secondary methods involve using existing data that have already been collected
by others.
a. Document Review
Analyzing existing documents such as reports, books, and articles.
Advantages: Cost-efficient and time-saving.
Examples: Reviewing annual business reports, analyzing historical
archives.
b. Data from Online Databases
Accessing pre-collected data from reputable online sources.
Advantages: Extensive and readily available.
Examples: World Bank datasets, census data, and scientific databases like
PubMed.
c. Meta-Analysis
Synthesizing data from multiple studies to draw overarching conclusions.
Advantages: Comprehensive and robust.
Examples: Combining studies on climate change impacts, meta-analyses in
healthcare.
Sampling Techniques
In any research endeavor, the population represents the entire set of
individuals, events, or data points about which the researcher intends to draw
conclusions. For instance, in a study examining college students’ stress levels,
the population may consist of all students currently enrolled in a specific
university. However, studying an entire population is often impractical due to
constraints of time, cost, and logistics. To address this challenge, researchers
select a sample, a subset of the population, which ideally reflects its key
characteristics (Shaughnessy, Zechmeister, & Zechmeister, 2014).
A. Probability Sampling
Probability sampling ensures that every member of the population has a known,
non-zero chance of being selected, enhancing the representativeness of the
sample. This technique is vital when the research aims to generalize findings to a
broader population (Singh, 2006).
. Simple Random Sampling: Every member of the population has an equal
chance of being selected. This method often uses random number tables or
computerized generators to minimize selection bias (Shaughnessy et al.,
2014, p. 138).
. Stratified Random Sampling: The population is divided into homogeneous
subgroups (strata) such as age, gender, or income levels, from which
samples are drawn randomly. This ensures that key subgroups are
adequately represented in the sample (Singh, 2006).
. Cluster Sampling: The population is divided into naturally occurring groups
(clusters), such as schools or geographical regions. Entire clusters are
selected randomly, which can be cost-effective for large populations, albeit at
the expense of potential intra-cluster similarities (Shaughnessy et al., 2014).
B. Non-Probability Sampling
Non-probability sampling does not provide every individual in the population
with a known chance of selection, often resulting in sampling bias (Singh, 2006).
. Convenience Sampling: Participants are selected based on their
availability or accessibility. While convenient and inexpensive, this method
may lead to unrepresentative samples (Shaughnessy et al., 2014, p. 138).
. Purposive Sampling: Researchers select participants who possess specific
characteristics relevant to the study. This method is valuable for exploratory
research or qualitative inquiries (Singh, 2006).
. Snowball Sampling: Participants recruit others into the study. This
technique is often used in hard-to-reach populations but can result in biased
samples if initial recruits are not diverse (Shaughnessy et al., 2014).
References
Creswell, J. W., & Creswell, J. D. (2018). Research Design: Qualitative, Quantitative, and
Mixed Methods Approaches (5th ed.). Sage Publications.
Bryman, A. (2016). Social Research Methods (5th ed.). Oxford University Press.
Flick, U. (2018). An Introduction to Qualitative Research (6th ed.). Sage Publications.
Shaughnessy, J. J., Zechmeister, E. B., & Zechmeister, J. S. (2014). Research methods in
psychology (10th ed.). McGraw-Hill Education.
Singh, A. K. (2006). Tests, measurements and research methods in behavioural
sciences (5th ed.). Bharati Bhawan.
