Assignment no. 1
STA630
Scenario:
The recent monsoon has affected the Sindh province particularly
Karachi which recorded the heaviest rainfall measuring 74.3mm. Rain floods have
affected the residential and commercial areas, damaging properties and
disrupting the power and telecommunication system. The intensity of the rain is
likely to be increased and continued for the next few weeks. The Pakistan
Meteorological Department (PMD) wants to collect data from the people who got
injured by the recent rain floods in the residential areas of Karachi. The
purpose is to list the hardships, financial losses, and dislocation of
families.
PMD in this regard has hired the services of a researcher to
conduct a study and collect data from such people. Quick and efficient data is
required in this regard. Initially, the research retried to collect the data
from unions and hospitals in the affected areas in order to gather data but,
both entities showed non-corporation and reluctance to provide the list of
people because of security and privacy reasons. The list of people is also
incomplete thus the dataset was not reliable.
While keeping issues of
difficulty in accessing people due to destroyed infrastructure and lack of
data, the researcher is planning to collect the data from the affected people
who are easily available by directly visiting the hospital wards.
The results of the study will be of utmost importance for the PMD
to take immediate necessary actions for the affected people.
REQUIREMENTS:
Being a student of Research, you are required to answer the
following questions:
1. Which Non-Probability Sampling Technique should be adopted by
the researcher in the given scenario? (Marks: 2)
2. Give two justifications in this regard. (Marks:4+4=8)
1.
Which
Non-Probability Sampling Technique should be adopted by the researcher in the
given scenario?
Answer:-
Convenience sampling
2.
Give two justifications in this regard.
Researchers
use various sampling techniques
in situations where there are large populations. In most cases, testing the
entire community is practically impossible because they are not easy to reach.
Researchers use convenience sampling in situations where additional inputs are
not necessary for the principal research. There are no criteria required to be
a part of this sample. Thus, it becomes incredibly simplified to include
elements in this sample. All components of the population are eligible and
dependent on the researcher’s proximity to get involved in the sample.
v Convenience sampling is
applied by brands and organizations to measure their perception of their image
in the market. Data is collected from potential customers to understand
specific issues or manage opinions of a newly launched product. In some cases,
it is the only available option. For example, a university student working on a
project and wants to understand the average consumption of soda on campus on a
Friday night will most possibly call his/her classmates and friends and ask how
many cans of soda they consume. Or may go to a party nearby and conduct an easy
survey. There is always a chance that the randomly selected population may not
accurately represent the population of interest, thus increasing the chances of
bias.
·
A basic
example of a convenience sampling method is when companies distribute their
promotional pamphlets and ask questions at a mall or on a crowded street with
randomly selected participants.
·
Businesses
use this sampling method to gather information to address critical issues
arising from the market. They also use it when collecting feedback about a
particular feature or a newly launched product from the sample created.
·
During
the initial stages of survey research, researchers usually prefer using
convenience sampling as it’s quick and easy to deliver results. Even if many
statisticians avoid implementing this technique, it is vital in situations
where you intend to get insights in a shorter period or without investing too
much money.
v
Top
six advantages of using convenience sampling
Here are the advantages of adopting a
convenience sampling approach:
1.
Collect
data quickly: In situations
where time is a constraint, many researchers choose this method for quick data
collection. The rules to gather elements for the sample are least complicated
in comparison to techniques such as simple random sampling, stratified sampling,
and systematic sampling.
Due to this simplicity, data collection takes minimal time.
2.
Inexpensive
to create samples: The money and
time invested in other probability sampling methods are quite large compared to
convenience sampling. It allows researchers to generate more samples with less
or no investment and in a brief period.
3.
Easy
to do research: The name of
this surveying technique clarifies how samples are formed. Elements are easily
accessible by the researchers and so, collecting members for the sample becomes
easy.
4.
Low
cost: Low cost is one
of the main reasons why researchers adopt this technique. When on a small
budget, researchers – especially students, can use the budget in other areas of
the project.
5.
Readily
available sample: Data collection
is easy and accessible. Most convenience sampling considers the population at
hand. Samples are readily available to the researcher. They do not have to move
around too much for data collection. Quotas are
met quickly, and the data collection can commence even within a few hours.
6.
Fewer
rules to follow: It doesn’t
require going through a checklist to filter members of an audience. Here,
gathering critical information and data becomes uncomplicated. For instance, if
an NGO wants to survey women’s empowerment, they can go to schools, colleges,
offices, etc. in their proximity and gather quick responses.