Assignment -4 BRM

1. Differentiate between primary data and secondary data.

Explain the various techniques of collecting primary data.
2. Define the term Questionnaire. Explain its merits and
demerits. What are the characteristics of a good
questionnaire.
3. Define the term sampling design. Discussvarious types
ofsampling design with relevant examples.

1 .Ans; Data collection plays a very crucial role in the statistical

analysis. In research, there are different methods used to gather
information, all of which fall into two categories, i.e. primary data, and
secondary data. As the name suggests, primary data is one which is
collected for the first time by the researcher while secondary data is the
data already collected or produced by others.

Definition of Primary Data

Primary data is data originated for the first time by the researcher
through direct efforts and experience, specifically for the purpose of
addressing his research problem. Also known as the first hand or raw
data. Primary data collection is quite expensive, as the research is
conducted by the organisation or agency itself, which requires resources
like investment and manpower. The data collection is under direct
control and supervision of the investigator.
The data can be collected through various methods like surveys,
observations, physical testing, mailed questionnaires, questionnaire
filled and sent by enumerators, personal interviews, telephonic
interviews, focus groups, case studies, etc.

Definition of Secondary Data

Secondary data implies second-hand information which is already

collected and recorded by any person other than the user for a purpose,
not relating to the current research problem. It is the readily available
form of data collected from various sources like censuses, government
publications, internal records of the organisation, reports, books, journal
articles, websites and so on.

Key Differences Between Primary and Secondary Data

The fundamental differences between primary and secondary data are

discussed in the following points:

1. The term primary data refers to the data originated by the

researcher for the first time. Secondary data is the already existing
data, collected by the investigator agencies and organisations
earlier.
2. Primary data is a real-time data whereas secondary data is one
which relates to the past.
3. Primary data is collected for addressing the problem at hand while
secondary data is collected for purposes other than the problem at
hand.
4. Primary data collection is a very involved process. On the other
hand, secondary data collection process is rapid and easy.
5. Primary data collection sources include surveys, observations,
experiments, questionnaire, personal interview, etc. On the
contrary, secondary data collection sources are government
publications, websites, books, journal articles, internal records etc.
 6. Primary data collection requires a large amount of resources like
time, cost and manpower. Conversely, secondary data is relatively
inexpensive and quickly available.
7. Primary data is always specific to the researcher’s needs, and he
controls the quality of research. In contrast, secondary data is
neither specific to the researcher’s need, nor he has control over
the data quality.
8. Primary data is available in the raw form whereas secondary data
is the refined form of primary data. It can also be said that
secondary data is obtained when statistical methods are applied to
the primary data.
9. Data collected through primary sources are more reliable and
accurate as compared to the secondary sources.

2.Ans; A questionnaire is a research instrument that consists of a set of

questions or other types of prompts that aims to collect information from
a respondent. A research questionnaire is typically a mix of close-ended
questions and open-ended questions.

Open-ended, long-form questions offer the respondent the ability to

elaborate on their thoughts. Research questionnaires were developed in
1838 by the Statistical Society of London.

The data collected from a data collection questionnaire can be

both qualitative as well as quantitative in nature. A questionnaire may or
may not be delivered in the form of a survey, but a survey always
consists of a questionnaire.

Advantages of the Questionnaire Method:

1. Saves Time of the Researchers

The questionnaire method is the most time-saving method when trying to collect primary
data. This is because the researchers do not need to physically conduct face to face
interviews of the respondents (such as when conducting surveys). The researchers only
need to take out some time to mail the questions. The respondents can then fill out and
return the forms in due course of time.

2. Less expenditure
The researcher needs to spend very little money to collect data via a questionnaire. In
case the researcher is sending the questionnaire via post, only the postal fees need to be
paid. If the researcher is sending an email, then the data collection can be done practically
free of cost.

3. Requires less Manpower

When conducting a survey, a lot of manpower is required because the researcher needs to
hire people to conduct face to face interviews. This is not the case for the questionnaire
method. The questionnaire method only needs some people who can organize and
interpret the collected data.

4. No Personal Bias
When oral interviews are conducted, it has been observed that the respondents might
sometimes be subtly led to answer according to the personal bias of the investigator. This
element of personal bias is completely eliminated by sending questionnaires because the
respondents fill out the answers on their own. Hence such answers will be more authentic
and accurate.

5. Data can be collected over a Large Area

Suppose you want to study the eating habits of people living in a particular city. Asking
people in person would be impractical and it would be impossible to cover the entire
population of the city. Here, we can widen our area of investigation by simply sending
questions via mail and requesting people to respond.

6. Ideal Method for Respondents who are Introverted

Some people are introverted and hold back from giving their true opinion to other people.
Such people are much more likely to give honest answers when they are asked to write
them down.
7. Identity of Respondents is Protected
If people are asked questions about controversial issues they may be reluctant to state
their views. Therefore whenever a questionnaire is sent out, the respondents are assured
that their identities will be protected. Since the respondents provide answers
anonymously their responses are much more likely to be truthful.

8. Data Obtained is Simple to Interpret

The questions asked in a questionnaire are usually YES/NO type of questions where only
a few responses are possible. It is very easy for the researcher to organize and interpret
such simple kinds of data.

Disadvantages of the Questionnaire Method:

1. Low degree of Reliability:

Some people may be careless when filling out the questionnaire and the data so collected
may not be completely accurate. Thus the data obtained cannot be said to be completely
reliable.

2. Respondents must be Literate:

This is the main drawback of the questionnaire method. For example, when conducting a
study of people living in a remote village in India it is highly probable that the residents
of the village may not be literate. If the respondents are not literate they will not be able
to read the questions or provide answers.

3. Non Response
Many people on receiving the questionnaire might simply ignore it or decline to provide
answers simply because they may not be interested. The respondents might not have the
motivation to take out some time to fill out the answers carefully. If the rate of non-
response is high then it will introduce errors in the study

4. Reluctance to provide Personal Information:

People may be hesitant to provide a written record of information such as their income
and personal habits. This can happen even if the people are assured that the data will be
anonymized and their identities protected.
5. Incomplete Answers:
Many people when filling out the questionnaire do not provide answers to all the
questions. They might answer some questions and leave other questions blank.
Sometimes the answers provided may be vague or hard to interpret. Such responses then
become unuseable.

6. Bias/Untruthfullness of Respondents:
Some respondents might choose to deliberately provide incorrect information when
providing answers. The researcher has no way to cross-check or verify whether the
responses are accurate. The researcher is completely dependent on the hope that
respondents respond truthfully.

7. Only Simple Minded Questions can be Asked:

Since the questions asked in a questionnaire are usually YES/NO type of questions
there is no scope for nuance. It is much better to conduct personalized interviews to
know about a person’s views on nuanced topics. It is much easier to understand a
person’s emotions and thoughts in a personalized setting.

Characteristics of good questionaire:

1 Short in terms of the number and length of questions

2 Simple and easily understood

3 Avoid personal and sensitive matters

4 Elicit the data and information required

5 Questions must be orderly and systematically laid out

6 Clear instructions with respect to completing the questionnaire

7 Avoid ambiguous questions

8 Questions must not lead to a certain answer

3.Ans: A sample design is a definite plan for obtaining a sample from a
given population. It refers to the technique or the procedure the
researcher would adopt in selecting items for the sample. Sample design
also leads to a procedure to tell the number of items to be included in the
sample i.e., the size of the sample. Hence, sample design is determined
before the collection of data. Among various types of sample design
technique, the researcher should choose that samples which are reliable
and appropriate for his research study.
When you conduct research about a group of people, it’s rarely possible
to collect data from every person in that group. Instead, you select a
sample. The sample is the group of individuals who will actually
participate in the research.

To draw valid conclusions from your results, you have to carefully

decide how you will select a sample that is representative of the group as
a whole. There are two types of sampling methods:

• Probability sampling involves random selection, allowing you to

make strong statistical inferences about the whole group.
• Non-probability sampling involves non-random selection based
on convenience or other criteria, allowing you to easily collect
data.

Probability sampling is a sampling technique in which

researchers choose samples from a larger population using a
method based on the theory of probability. This sampling method
considers every member of
the population and forms samples based on a fixed process.
 For example, in a population of 1000 members, every member will
have a 1/1000 chance of being selected to be a part of a sample.
Probability sampling eliminates sampling bias in the population and
gives all members a fair chance to be included in the sample.

Four types of non-probability sampling explain the purpose of this

sampling method in a better manner:

Convenience sampling: This method is dependent on the ease of access

to subjects such as surveying customers at a mall or passers-by on a busy
street. It is usually termed as convenience sampling, because of the
researcher’s ease of carrying it out and getting in touch with the subjects.
Researchers have nearly no authority to select the sample elements, and it’s purely
done based on proximity and not representativeness. This non-probability sampling
method is used when there are time and cost limitations in collecting feedback. In
situations where there are resource limitations such as the initial stages of research,
convenience sampling is used.
For example, startups and NGOs usually conduct convenience sampling at a mall to
distribute leaflets of upcoming events or promotion of a cause – they do that by
standing at the mall entrance and giving out pamphlets randomly.
• Judgmental or purposive sampling: Judgemental or purposive samples are
formed by the discretion of the researcher. Researchers purely consider the
purpose of the study, along with the understanding of the target audience. For
instance, when researchers want to understand the thought process of people
interested in studying for their master’s degree. The selection criteria will be:
“Are you interested in doing your masters in …?” and those who respond with a
“No” are excluded from the sample.
• Snowball sampling: Snowball sampling is a sampling method that researchers
apply when the subjects are difficult to trace. For example, it will be extremely
challenging to survey shelterless people or illegal immigrants. In such cases,
using the snowball theory, researchers can track a few categories to interview
and derive results. Researchers also implement this sampling method in
situations where the topic is highly sensitive and not openly discussed—for
example, surveys to gather information about HIV Aids. Not many victims will
readily respond to the questions. Still, researchers can contact people they might
know or volunteers associated with the cause to get in touch with the victims and
collect information.
• Quota sampling: In Quota sampling, the selection of members in this sampling
technique happens based on a pre-set standard. In this case, as a sample is
formed based on specific attributes, the created sample will have the same
qualities found in the total population. It is a rapid method of collecting samples.