Practical Research 1a
Practical Research 1a
Practical Research 1a
Definition
In research, sampling is a word that refers to your method or process of selecting respondents or
people to answer questions meant to yield data for a research study. The chosen ones constitute the
sample through which you will derive facts and evidences to support the claims or conclusions
propounded by your research problem. The bigger group from where you choose the sample is called
population, and sampling frame is the term used to mean the list of the members of such population
from where you will get the sample. (Paris 2013)
History
The beginning of sampling could be traced back to the early political activities of the Americans
in 1920 when Literary Digest did a pioneering survey about the American citizens favorite among the
1920 presidential candidates. This was the very first survey that served as the impetus from the
discovery by academic researchers of other sampling strategies that they categorized into two classes:
probability sampling or unbiased sampling and non-probability sampling. (Babbie 2013)
A sampling error crops up if the selection does not take place in the way it is planned. Such
sampling error is manifested by strong dissimilarity between the sample and the ones listed in the
sampling frame. (P) How numerous the sampling errors are depends on the size of the sample. The
smaller the sample is, the bigger than number of sampling errors. Thus, choose to have a bigger sample
of respondents to avoid sampling errors. However, deciding to increase the size of your sample is not so
easy. There are these things you have to mull over in finalizing about this such as expenses for
questionnaires and interview trips, interview schedules, and time for reading respondents answers.
The right sample size also depends on whether or not the group is heterogeneous or
homogeneous. The first group requires a bigger size; the second, a smaller one. For a study in the field of
social sciences requiring an in-depth investigation of something such as one involving the national
government, the right sample size ranges from 1,000 to 1,500 or up to 2,500. On the other hand,
hundreds, not thousands, of respondents suffice for a study about any local government unit. (Suter
2012; Emmel 2013)
Types of Probability
1. Simple Random Sampling
Simple random sampling is the best type of probability sampling through which you can
choose sample from a population. Using pure-chance selection, you assure every
member the same opportunity to be in the sample. Here, the only basis of including or
excluding a member is by chance or opportunity, not by any occurrence accounted for by
cause-effect relationships. Simple random sampling happens through any of these two
methods: (Burns 2012)
1.) Have a list of all members of the population; write each name on a card, and choose
cards through a pure-chance selection.
2.) Have a list of all members; give a number to member and then use randomized or
unordered numbers in selecting names from the list.
2. Systematic Sampling
For this kind of probability sampling, chance and system are the ones to determine who
should compose the sample. For instance, if you want to have a sample of 150, you may
select a set a number like 1 to 15, and out of a list of 1,500 students, take every 15 th
name on the list until you complete the total number respondents to constitute your
sample.
3. Stratified Sampling
The group comprising the sample is chosen in a way that such group is liable to
subdivision during the data analysis stage. A study needing group by-group analysis finds
stratified sampling the right probability sampling to use.
4. Cluster Sampling
this is a probability sampling that makes you isolate a set of persons instead of individual
members to serve as sample members. For example, if you want to have a sample of 120
out of 1,000 students, you can randomly select three sections with 40 students each to
constitute the sample.
Non-Probability Sampling
Non-probability sampling disregards random selection of subjects. The subjects are chosen
based on their availability or the purpose of the study, and in some cases, on the sole discretion of the
researcher. This is not a scientific way of selecting respondents. Neither does it offer a valid or an
objective way of detecting sampling errors. (Edmond 2013)
INTERVIEW
Definition
In research, interview is a data gathering technique that makes you
verbally ask the subjects or respondents questions to give answers to what your
research study is trying to look for. Done mostly in qualitative research studies,
interview aims at knowing what the respondents think and feel about the topic
of your research.
Traditionally viewed, this data gathering technique occurs between you,
the researcher , and your respondents in a face-to-face situation. In this case,
you speak directly with your respondent, individually or collectively. On the
other hand, by using electronic and technological communication devices like
Internet, mobile phones, email, etc., interview can be considered as a modern
tool of research. All in all, be it a traditional or a modern type of interview, it is
a conversation with a purpose that gives direction to the question-answer
activity between the interviewer and the interviewee. (Babbie2014, p. 137;
Rubin 2011)
Types
1. Structured Interview
This is an interview that requires the use of an interview schedule or a list of
questions answerable with one and only item from a set of alternative responses.
Choosing one answers, the respondents are barred from giving answers that reflect their
own thinking or emotions about the topic. You, the researcher, are completely pegged at
the interview schedule or prepared list of questions.
2. Unstructured Interview
In this type of interview, the respondents answer the questions based on what
they personally think and feel about it. There are no suggested answers. They purely
depend on the respondents decision-making skills, giving them opportunity to think
critically about the question.
3. Semi-Structured Interview
The characteristics of the first two types are found in the third type of interview
called semi-structured interview. Here, you prepare a schedule or a list of questions that
is accompanied by a list of expressions from where the respondents can pick out the
correct answer. However, after choosing one from suggested answers, the respondents
answer another set of questions to make them explain the reason s behind their choices.
Allowing freedom for you to change the questions and for the respondents to think of
their own answers, this semi-structured interview is a flexible and an organized type of
interview. (Rubin 2012; Bernard 2013)
Approaches
1. Individual Interview
Only one respondent is interviewed here. The reason behind this one-
on-one interview is the lack of trust the interviewees have among themselves.
One example of this is the refusal of one interviewee to let other interviewees
get a notion of or hear his or her responses to the questions. Hence, he or she
prefers to have an individual interview because you have to interview a group of
interviewees one by one.
2. Group Interview
In this interview approach, you ask the question not to one person, but
to a group of people at the same time. The group members take turns in
answering the question. This approach is often used in the field of business,
specifically in marketing research. Researchers in this field, whose primary aim
in adhering to this interview approaching is to know peoples food preferences
and consumer opinions; they also call this as focus group interview. The chances
of having some respondents getting influenced by the other group members are
one downside of this interview approach. (Denzin 2013; Feinberd 2013)
3. Mediated Interview
No face-to-face interview is true for this interview approach because
this takes place through electronic communication devices such as telephones,
mobile phones, email, among others. Though mediated interview disregards
non-verbal communication (e.g., bodily movements, gestures facial expressions,
feelings, eye contact, etc.), many, nonetheless, consider this better because of
the big number of respondents it is capable of reaching despite the cost,
distance, and human disabilities affecting the interview.
It is a synchronous mediated interview if you talk with the subjects
through the telephone, mobile phone, or online chat and also find time to see
each other. It is asynchronous only two persons are inter viewed at a different
time through the Internet, email, Facebook, Twitter, and other social network
media. (Goodwin 2014; Barbour 2014)
Questionnaire
A questionnaire is a paper containing a list of questions including the specific place and
space in the paper where you write the answers to the questions. This prepared set of questions
elicits factual or opinionated answers from the respondents through his or her acts of checking
one chosen answer from several options or of writing on a line provided fro any opinionated
answer.
Purposes of a Questionnaire
1. To discover peoples thought and feelings about the topic of the research
2. To assist you in conducting an effective face-to-face interview with your
respondents
3. To help you plan how to obtain and record the answers to your questions
4. To make the analysis, recording, and coding of data easier and faster
Types of Questionnaire
1. Postal questionnaire
As the name connotes, this type of questionnaire goes to the
respondent through postal service or electronic mail. It is through the mail or
postal system that the accomplished questionnaires will be sent back to the
researcher. In some cases, the researcher can personally collect finished
questionnaires.
2. Self-administered questionnaire
This kind of questionnaire makes you act as the interviewer and the
interviewee at the same time. First, you ask the questions either in person or
through phone; then, you will be writing the interviewees answers on a piece of
paper. A questionnaire like this fits a structured kind of interview. (Barbour
2014)
Advantages
1. It is cheap as it does not require you to travel to hand the questionnaire a big
number of respondents in faraway places.
2. It entails an easy distribution to respondents.
3. It offers more opportunity for the respondents to ponder on their responses.
4. It enables easy comparison of answers because of a certain degree of uniformity
among the questions.
5. It has the capacity to elicit spontaneous or genuine answers from the
respondents.
Disadvantages
1. There is a possibility that some questions you distributed do not go back to you,
and this prevents you from getting the desired rate of responses.
2. Confusing and uninteresting questions to respondents fail to elicit the desired
responses.
3. Owing to individual differences between the selected subjects and those in the
population, in general, the questionnaire is hard up in obtaining
unbiased results to represent the characteristics of the target population.
4. It prevents you from being with the respondents physically to help them unlock
some difficulties in their understanding of the questions.
DATA ANALYSIS
Nature
Data analysis is a process of understanding data or known facts or assumptions serving
as the basis of any claims or conclusions you have about something. You collect these data in
many ways: observation, interview, documentary analysis, and research instruments like
questionnaires, tests, etc. Your primary aim in analyzing recorded data is to find out if they exist
or operate to give answer to the research questions you raised prior to your acts of collecting
them.
In analyzing data, you go through coding and collating. Coding is your act of using
symbols like letters or words to represent arbitrary or subjective data (emotions, opinions,
attitudes) to ensure secrecy or privacy of the data. Collating, on the other hand, is your way of
bringing together the coded data. Giving the data an orderly appearance is putting them in a
graph, specifically a table of responses.
Data matrix
The term data matrix is also used to name this table of responses that consists of table
of cases and their associated variables. This data matrix is of two types: the profile matrix that
shows measurements of variables or factors for a set of cases or respondents and the proximity
matrix that indicates measurements of similarities and differences between items. Under
proximity matrix, if the measurements show how alike things are, it is called similarity matrix. If
they show how different they are, it is called dissimilarity matrix. (Denzin 2013)