MAPC ASSIGNMENT 2023-2024
MPC-005 RESEARCH METHODS
SECTION – A
1. Define sampling. Discuss the different methods of sampling.
A. Sampling is a fundamental concept in statistics and research methodology, particularly in fields
such as psychology, sociology, education, and health sciences. It refers to the process of
selecting a subset (sample) from a larger group (population) to estimate characteristics of the
whole group. Since studying an entire population is often impractical due to time, cost, and
logistical constraints, sampling provides a practical means of data collection and analysis.
According to Kerlinger (1986), sampling is the process of selecting units (e.g., people,
organizations) from a population of interest so that by studying the sample we may fairly
generalize our results back to the population from which they were chosen.
In simple terms, sampling allows researchers to draw inferences about the population without
having to investigate every individual. The key is that the sample must be representative of the
population, so that conclusions drawn from the sample can be generalized with reasonable
accuracy.
Types of Sampling Methods
Sampling methods can broadly be divided into two major categories:
1. Probability Sampling
2. Non-Probability Sampling
Each of these categories includes several techniques suited to different types of research
designs and goals.
1. Probability Sampling Methods
In probability sampling, every member of the population has a known, non-zero chance of being
selected. This approach increases the likelihood of the sample being representative of the
population, thereby enhancing the validity and reliability of the results.
a) Simple Random Sampling
In this method, every individual in the population has an equal chance of being selected.
Selection is typically done using random number generators or drawing lots.
Advantages: High representativeness, minimal bias.
Disadvantages: Requires a complete list of the population, which may not be feasible for
large populations.
Example: Drawing 50 students randomly from a university student registry to study stress levels.
b) Systematic Sampling
,In systematic sampling, every kth individual is selected from a list of the population after a
random starting point is chosen.
Advantages: Simpler than simple random sampling, especially for large populations.
Disadvantages: If the list has a pattern, it might introduce bias.
Example: Selecting every 10th patient from a hospital admissions list.
c) Stratified Sampling
In stratified sampling, the population is divided into strata (subgroups) based on a characteristic
(e.g., age, gender, education), and a random sample is drawn from each stratum.
Advantages: Ensures representation of all key subgroups.
Disadvantages: More complex, requires detailed population information.
Example: Sampling 30 students each from undergraduate, postgraduate, and doctoral levels for
a study on learning habits.
d) Cluster Sampling
The population is divided into clusters (usually based on geography or institutions), and entire
clusters are randomly selected.
Advantages: Cost-effective and practical for large, spread-out populations.
Disadvantages: Higher sampling error if clusters are not homogeneous.
Example: Selecting 5 schools randomly from a district and then surveying all students in those
schools.
2. Non-Probability Sampling Methods
In non-probability sampling, not all individuals have a known or equal chance of being selected.
These methods are often used in qualitative research or when probability sampling is not
feasible.
a) Convenience Sampling
Participants are selected based on their availability and willingness to participate.
Advantages: Quick and easy.
Disadvantages: High risk of bias; not representative.
Example: Interviewing people at a mall for a marketing survey.
b) Purposive (Judgmental) Sampling
The researcher selects participants based on their knowledge or expertise relevant to the
research.
Advantages: Useful for specialized research topics.
Disadvantages: Subjective; lacks generalizability.
Example: Selecting therapists with over 10 years of experience to study treatment effectiveness.
, c) Snowball Sampling
Used when the population is hard to access; initial participants refer others who meet the
criteria.
Advantages: Effective for hidden or hard-to-reach populations.
Disadvantages: Risk of homogeneity; bias due to network limitations.
Example: Studying drug users or undocumented migrants.
d) Quota Sampling
The researcher selects participants based on specific quotas (e.g., age, gender) to match certain
characteristics of the population.
Advantages: Ensures some representativeness.
Disadvantages: Not random; introduces selection bias.
Example: Ensuring 50% male and 50% female participants in a health behavior study.
Importance of Sampling in Research
Cost-effectiveness: Studying a sample is more economical than studying the whole
population.
Time-saving: Collecting data from a smaller group is quicker.
Feasibility: Sometimes it is physically or ethically impossible to study everyone.
Accuracy: Proper sampling techniques can yield highly accurate estimates of population
parameters.
Generalization: When done correctly, sampling allows researchers to generalize findings
from the sample to the broader population.
Sampling is an indispensable part of the research process. It allows researchers to draw
conclusions about a population without studying every individual. The choice between
probability and non-probability sampling depends on the nature of the research, the resources
available, and the required accuracy of results. While probability sampling offers greater
reliability and generalizability, non-probability sampling is useful in exploratory, qualitative, or
hard-to-reach population studies. Researchers must carefully choose the sampling method best
suited to their research objectives to ensure meaningful and valid results.
2. Discuss the steps involved in research process.
A. Research is a systematic and scientific approach to discovering new knowledge, validating existing
theories, or solving specific problems. In any discipline — be it psychology, education, sociology,
medicine, or business — the research process ensures that investigations are methodical,
objective, and replicable. To achieve valid and reliable results, researchers follow a structured
sequence of steps, commonly referred to as the research process.
The steps involved in the research process can be grouped into eight major stages:
MPC-005 RESEARCH METHODS
SECTION – A
1. Define sampling. Discuss the different methods of sampling.
A. Sampling is a fundamental concept in statistics and research methodology, particularly in fields
such as psychology, sociology, education, and health sciences. It refers to the process of
selecting a subset (sample) from a larger group (population) to estimate characteristics of the
whole group. Since studying an entire population is often impractical due to time, cost, and
logistical constraints, sampling provides a practical means of data collection and analysis.
According to Kerlinger (1986), sampling is the process of selecting units (e.g., people,
organizations) from a population of interest so that by studying the sample we may fairly
generalize our results back to the population from which they were chosen.
In simple terms, sampling allows researchers to draw inferences about the population without
having to investigate every individual. The key is that the sample must be representative of the
population, so that conclusions drawn from the sample can be generalized with reasonable
accuracy.
Types of Sampling Methods
Sampling methods can broadly be divided into two major categories:
1. Probability Sampling
2. Non-Probability Sampling
Each of these categories includes several techniques suited to different types of research
designs and goals.
1. Probability Sampling Methods
In probability sampling, every member of the population has a known, non-zero chance of being
selected. This approach increases the likelihood of the sample being representative of the
population, thereby enhancing the validity and reliability of the results.
a) Simple Random Sampling
In this method, every individual in the population has an equal chance of being selected.
Selection is typically done using random number generators or drawing lots.
Advantages: High representativeness, minimal bias.
Disadvantages: Requires a complete list of the population, which may not be feasible for
large populations.
Example: Drawing 50 students randomly from a university student registry to study stress levels.
b) Systematic Sampling
,In systematic sampling, every kth individual is selected from a list of the population after a
random starting point is chosen.
Advantages: Simpler than simple random sampling, especially for large populations.
Disadvantages: If the list has a pattern, it might introduce bias.
Example: Selecting every 10th patient from a hospital admissions list.
c) Stratified Sampling
In stratified sampling, the population is divided into strata (subgroups) based on a characteristic
(e.g., age, gender, education), and a random sample is drawn from each stratum.
Advantages: Ensures representation of all key subgroups.
Disadvantages: More complex, requires detailed population information.
Example: Sampling 30 students each from undergraduate, postgraduate, and doctoral levels for
a study on learning habits.
d) Cluster Sampling
The population is divided into clusters (usually based on geography or institutions), and entire
clusters are randomly selected.
Advantages: Cost-effective and practical for large, spread-out populations.
Disadvantages: Higher sampling error if clusters are not homogeneous.
Example: Selecting 5 schools randomly from a district and then surveying all students in those
schools.
2. Non-Probability Sampling Methods
In non-probability sampling, not all individuals have a known or equal chance of being selected.
These methods are often used in qualitative research or when probability sampling is not
feasible.
a) Convenience Sampling
Participants are selected based on their availability and willingness to participate.
Advantages: Quick and easy.
Disadvantages: High risk of bias; not representative.
Example: Interviewing people at a mall for a marketing survey.
b) Purposive (Judgmental) Sampling
The researcher selects participants based on their knowledge or expertise relevant to the
research.
Advantages: Useful for specialized research topics.
Disadvantages: Subjective; lacks generalizability.
Example: Selecting therapists with over 10 years of experience to study treatment effectiveness.
, c) Snowball Sampling
Used when the population is hard to access; initial participants refer others who meet the
criteria.
Advantages: Effective for hidden or hard-to-reach populations.
Disadvantages: Risk of homogeneity; bias due to network limitations.
Example: Studying drug users or undocumented migrants.
d) Quota Sampling
The researcher selects participants based on specific quotas (e.g., age, gender) to match certain
characteristics of the population.
Advantages: Ensures some representativeness.
Disadvantages: Not random; introduces selection bias.
Example: Ensuring 50% male and 50% female participants in a health behavior study.
Importance of Sampling in Research
Cost-effectiveness: Studying a sample is more economical than studying the whole
population.
Time-saving: Collecting data from a smaller group is quicker.
Feasibility: Sometimes it is physically or ethically impossible to study everyone.
Accuracy: Proper sampling techniques can yield highly accurate estimates of population
parameters.
Generalization: When done correctly, sampling allows researchers to generalize findings
from the sample to the broader population.
Sampling is an indispensable part of the research process. It allows researchers to draw
conclusions about a population without studying every individual. The choice between
probability and non-probability sampling depends on the nature of the research, the resources
available, and the required accuracy of results. While probability sampling offers greater
reliability and generalizability, non-probability sampling is useful in exploratory, qualitative, or
hard-to-reach population studies. Researchers must carefully choose the sampling method best
suited to their research objectives to ensure meaningful and valid results.
2. Discuss the steps involved in research process.
A. Research is a systematic and scientific approach to discovering new knowledge, validating existing
theories, or solving specific problems. In any discipline — be it psychology, education, sociology,
medicine, or business — the research process ensures that investigations are methodical,
objective, and replicable. To achieve valid and reliable results, researchers follow a structured
sequence of steps, commonly referred to as the research process.
The steps involved in the research process can be grouped into eight major stages:
