Ch. 2. The Research Process.pptx

Introduction
 The research process shown below is a series of consecutive
steps. To make a logical, smooth, forward journey
continuously while doing research. In practice, research is far
more messy because of overlapping among these steps. It is
necessary to remember that all these steps constitute an
integrated, intricate whole.
 The process of gathering information for the purpose of
initiating, modifying or terminating a particular investment or
group of investments.

RESEARCH PROCESS
 Steps in research process :
Define
research
problem
Review of
literature
Formulating
hypothesis
Preparing
research
design
Data
collection
Data
analysis
Interpretation
and report
writing

Steps in research process:
1. Define Research Problem -There are two types of research problem, viz., those relate to states of nature
relationship between variables. Essentially two steps are involved in define research problem, viz., understanding
the problem thoroughly and rephrasing the same into meaningful terms from an point of view.
2. Review of Literature- Once the problem is define, a brief summary of it should be written down. It is compulsory for a
research worker writing a thesis for a Ph.D. degree to write a synopsis of topic and submit it to necessary committee
or the research board for approval.
3. Formulate Hypothesis- Formulate hypothesis is tentative assumption made in order to draw out and test its logical
or empirical consequences. Hypothesis should be very specific and limited to the piece of research in hand because
it has to be tested. The role of the hypothesis is to guide the researcher by delimiting the area of research and to
keep him on the right track.
4. Preparing the Research Design- The function of research design is to provide for the collection of relevant evidence
with minimal expenditure of effort, time and money. Research purpose may be grouped into four categories,
viz., (1) Exploration, (2) Description,(3) Diagnosis, and (4) Experimentation.
5. Data Collection- Primary data can be collected through: By Observation Through personal interview Through
telephone interview By mailing of questionnaires Through Schedules
6. Data Analysis- The analysis of data requires a number of closely related operations such as establishment of
categories. This stage mainly include :1. Coding2. Editing3. Tabulation
7. Step Seven- Interpretation and Report Writing Researcher has to prepare the report of what has been done by him.
Writing of report includes:1. the preliminary pages;2. the main text, and3. the end matter.

Define Research Problem/ Research
question
 A research problem is a specific issue, difficulty, contradiction, or gap in
knowledge that you will aim to address in your research. The type of
research problem you choose depends on your broad topic of interest and
the type of research you want to do.
 A Research problem is a question that a researcher wants to answer or a
problem that a researcher wants to solve.
 A research problem is an issues or a concern
that an investigator / researcher presents and
justifies in a research study.

 Selection of a research problem depends on several factors such as researcher’s
knowledge, skills, interest, expertise, motivation & creativity with respect to the subject
chosen.
 A good research studies needs a lots of time for selection of research problem.
 Initially every researcher faces a predicament of identifying, selecting and formulating a good
research problem.
DEFINITION • “ A situation for which we have no ready & successful response by instinct or by
previous acquired habit. We must find out what to do”, i.e. the solution can be found out only
after an investigation. R.S. Woodworth.
 In others words, a research problem is an area of concern where there is a gap in the
knowledge base needed for professional practices.
 A research problem and problem statement are frequently used as synonyms. • However
there are a lot of difference between them.

 Why is the research problem important?
Without a well-defined research problem, you are likely to
end up with an unfocused and unmanageable project. You
might end up repeating what other people have already
said. You need a problem in order to do research that
contributes new and relevant insights. The research
problem is the first step towards knowing exactly what you’ll
do and why.

Step 1: Identify a broad problem area
As you discuss and read about your topic, look for under-explored aspects and areas of
concern, conflict or controversy. Your goal is to find a gap that your research project can fill.
Look for:
 Issues with performance or efficiency in an organization
 Processes that could be improved in an institution
 Areas of concern among practitioners in a field
 Difficulties faced by specific groups of people in society
If your research is connected to a job or internship, you will need to find a research problem
that has practical relevance for the organization.
Examples of practical research problems
 Department A of Company B has a high staff turnover rate, affecting productivity and team cohesion.
 Non-profit organization Y faces a funding gap that means some of its programs will have to be cut.

Step 2: Learn more about the problem
You have to find out what is already known about the problem, and pinpoint the exact aspect
that your research will address.
 Context and background
• Who does the problem affect?
• Has it been an issue for a long time, or is it a newly discovered problem?
• What research has already been done?
• Have any solutions been proposed?
• What are the current debates about the problem, and what do you think is missing from them?
 Specificity and relevance
• What particular place, time and/or people will you focus on?
• What aspects will you not be able to tackle?
• What will be the consequences if the problem is not resolved?
• Whose will benefit from resolving the problem (e.g. the management of an organization or future researchers)?
 Example of a specific research problem
 Non-profit organization X has been focused on retaining its existing support base, but lacks understanding of
how best to target potential new donors. To be able to continue its work, the organization requires research into
more effective fundraising strategies.
 When you have narrowed down your problem, the next step is to formulate a problem statement and research
questions or hypotheses.

COMPONENTS OF A RESEARCH
PROBLEM
A research problem has 6 components. • They are as follows…
1. Relevance of the study.
2. Title of the study.
3. Operational definitions of the variables.
4. Objectives of the study.
5. Delimitations of the study.
6. Scope & limitations of the study.

SOURCES OF RESEARCH PROBLEM
The common sources of research problem are as follows.
1. Personal experience.
2. Practical experience.
3. critical appraisal of literature.
4.Previous research.
5. existing theories.
6. Social issues.
7. Brainstorming.
8. Intuition.
9. Folklores.
10. Exposure to field situation.
11. Consultation with experts.

Designing the study
It is a plan consisting of a researcher’s decisions regarding sampling, data collection and data
analysis. More specifically, given that problem / hypothesis formulation and definition of concepts
are complete, it involves deciding the following aspects:
1. What are the types of data needed?
2. Where will the necessary data be found?
3. Where will the study be carried out?
4. How much material or how many cases will be necessary?
5. What will be the techniques for collecting data?
6. How will data be analysed?
7. How to best answer the above questions so as to minimise the expenditure of time, effort and money?
By thinking about the above questions the researcher prepares himself to overcome difficulties and
enhances prospects of reaching his goals without straying into unnecessary areas. Careful
research design ensures that research will not fail. So in this step, the researcher sits back and
thinks about techniques for data collection, their reliability and validity, method of drawing a sample
from universe, its size, organisation and analysis of data that are collected, practical difficulties
that may arise necessitating compromises etc. Each of the above aspects will not have equal
importance in his thinking. Nor does he have to lay out, in writing, a detailed plan. However in this
stage he has to mentally prepare himself for the hard and at times, uncertain work that is to follow.

Population vs sample
• The population is the entire group that you want to draw conclusions about.
• The sample is the specific group of individuals that you will collect data from.
The population can be defined in terms of geographical location, age, income, and many
other characteristics.
It can be very broad or quite narrow: maybe you want to make inferences about the whole
adult population of your country; maybe your research focuses on customers of a certain
company, patients with a specific health condition, or students in a single school.
It is important to carefully define your target population according to the
purpose and practicalities of your project.
If the population is very large, demographically mixed, and
geographically dispersed, it might be difficult to gain access to a
representative sample.

Sampling frame
The sampling frame is the actual list of individuals that the
sample will be drawn from. Ideally, it should include the entire
target population (and nobody who is not part of that
population).
Example
You are doing research on working conditions at Company X. Your population is
all 1000 employees of the company. Your sampling frame is the company’s HR
database which lists the names and contact details of every employee.

Sample Design
It is a plan consisting of a researcher’s decisions regarding sampling, data collection and data analysis.
More specifically, given that problem / hypothesis formulation and definition of concepts are complete, it
involves deciding the following aspects:
1. What are the types of data needed?
2. Where will the necessary data be found?
3. Where will the study be carried out?
4. How much material or how many cases will be necessary?
5. What will be the techniques for collecting data?
6. How will data be analyzed?
7. How to best answer the above questions so as to minimize the expenditure of time, effort and money?
By thinking about the above questions the researcher prepares himself to overcome difficulties and
enhances prospects of reaching his goals without straying into unnecessary areas. Careful research
design ensures that research will not fail. So in this step, the researcher sits back and thinks about
techniques for data collection, their reliability and validity, method of drawing a sample from universe, its
size, organization and analysis of data that are collected, practical difficulties that may arise necessitating
compromises

Sampling Methods
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 methods
Probability sampling means that every member of the
population has a chance of being selected. It is mainly used in
quantitative research. If you want to produce results that are
representative of the whole population, probability sampling
techniques are the most valid choice.
There are four main types of probability sample.

1. Simple random sampling
In a simple random sample, every member of the population has an equal
chance of being selected. Your sampling frame should include the whole
population.
To conduct this type of sampling, you can use tools like random number
generators or other techniques that are based entirely on chance.
Example
 You want to select a simple random sample of 100 employees of Company
X. You assign a number to every employee in the company database from 1
to 1000, and use a random number generator to select 100 numbers.
A random sample is one in which all members of a given population have the
same chances of being selected. Furthermore, the selection of each member
must be independent from the selection of any other members.

2. Systematic sampling
Systematic sampling is similar to simple random sampling, but it is usually slightly
easier to conduct. Every member of the population is listed with a number, but instead
of randomly generating numbers, individuals are chosen at regular intervals.
Example
 All employees of the company are listed in alphabetical order. From the first 10
numbers, you randomly select a starting point: number 6. From number 6 onwards,
every 10th person on the list is selected (6, 16, 26, 36, and so on), and you end up
with a sample of 100 people.
If you use this technique, it is important to make sure that there is no hidden pattern in
the list that might skew the sample. For example, if the HR database groups
employees by team, and team members are listed in order of seniority, there is a risk
that your interval might skip over people in junior roles, resulting in a sample that is
skewed towards senior employees.

3. Stratified sampling
Stratified sampling involves dividing the population into subpopulations that may differ
in important ways. It allows you draw more precise conclusions by ensuring that every
subgroup is properly represented in the sample.
To use this sampling method, you divide the population into subgroups (called strata)
based on the relevant characteristic (e.g. gender, age range, income bracket, job role).
Based on the overall proportions of the population, you calculate how many people
should be sampled from each subgroup. Then you use random or systematic sampling
to select a sample from each subgroup.
Example
The company has 800 female employees and 200 male employees. You want to
ensure that the sample reflects the gender balance of the company, so you sort the
population into two strata based on gender. Then you use random sampling on each
group, selecting 80 women and 20 men, which gives you a representative sample of
100 people.

4. Cluster sampling
Cluster sampling also involves dividing the population into subgroups, but each
subgroup should have similar characteristics to the whole sample. Instead of sampling
individuals from each subgroup, you randomly select entire subgroups.
If it is practically possible, you might include every individual from each sampled
cluster. If the clusters themselves are large, you can also sample individuals from
within each cluster using one of the techniques above.
This method is good for dealing with large and dispersed populations, but there is more
risk of error in the sample, as there could be substantial differences between clusters.
It’s difficult to guarantee that the sampled clusters are really representative of the
whole population.
Example
The company has offices in 10 cities across the country (all with roughly the same
number of employees in similar roles). You don’t have the capacity to travel to every
office to collect your data, so you use random sampling to select 3 offices – these are
your clusters.

Sample size
 The number of individuals you should include in your sample
depends on various factors, including the size and variability
of the population and your research design. There are
different sample size calculators and formulas depending on
what you want to achieve with statistical analysis.

Non-probability sampling
 Non-probability sampling is defined as a sampling technique in which the researcher selects
samples based on the subjective judgment of the researcher rather than random selection. It
is a less stringent method. This sampling method depends heavily on the expertise of the
researchers. It is carried out by observation, and researchers use it widely for qualitative
research.
 Non-probability sampling is a sampling method in which not all members of the population
have an equal chance of participating in the study, unlike probability sampling. Each member
of the population has a known chance of being selected. Non-probability sampling is most
useful for exploratory studies like a pilot survey (deploying a survey to a smaller sample
compared to pre-determined sample size). Researchers use this method in studies where it
is impossible to draw random probability sampling due to time or cost considerations.

Types of Non-probability sampling
 Quota sampling
With proportional quota sampling, the aim is to end up with a sample where the strata (groups) being studied (e.g., males vs. females students) are proportional to the
population being studied. If we were to examine the differences in male and female students, for example, the number of students from each group that we would include in
the sample would be based on the proportion of male and female students amongst the 10,000 university students. To understand more about quota sampling, how to create a
quota sample, and the advantages and disadvantages of this non-probability sampling technique, see the article: Quota sampling.
 Convenience sampling
A convenience sample is simply one where the units that are selected for inclusion in the sample are the easiest to access. In our example of the 10,000 university students, if
we were only interested in achieving a sample size of say 100 students, we may simply stand at one of the main entrances to campus, where it would be easy to invite the
many students that pass by to take part in the research. To understand more about convenience sampling, how to create a convenience sample, and the advantages and
disadvantages of this non-probability sampling technique, see the article: Convenience sampling.
 Purposive sampling
Purposive sampling, also known as judgmental, selective or subjective sampling, reflects a group of sampling techniques that rely on the judgement of the researcher when it
comes to selecting the units (e.g., people, cases/organisations, events, pieces of data) that are to be studied. These purposive sampling techniques include maximum variation
sampling, homogeneous sampling, typical case sampling, extreme (or deviant) case sampling, total population sampling and expert sampling. Each of these purposive
sampling techniques has a specific goal, focusing on certain types of units, all for different reasons. The different purposive sampling techniques can either be used on their
own or in combination with other purposive sampling techniques. To understand more about purposive sampling, the different types of purposive sampling, and the
advantages and disadvantages of this non-probability sampling technique, see the article: Purposive sampling.
 Self-selection sampling
Self-selection sampling is appropriate when we want to allow units or cases, whether individuals or organisations, to choose to take part in research on their own accord. The
key component is that research subjects (or organisations) volunteer to take part in the research rather than being approached by the researcher directly. To understand more
about self-selection sampling, how to create a self-selection sample, and the advantages and disadvantages of this non-probability sampling technique, see the article: Self-
selection sampling.
 Snowball sampling
Snowball sampling is particularly appropriate when the population you are interested in is hidden and/or hard-to-reach. These include populations such as drug addicts,
homeless people, individuals with AIDS/HIV, prostitutes, and so forth. To understand more about snowball sampling, how to create a snowball sample, and the advantages
and disadvantages of this non-probability sampling technique, see the article: Snowball sampling.
 Consecutive sampling:
This non-probability sampling method is very similar to convenience sampling, with a slight variation. Here, the researcher picks a single person or a group of a sample,
conducts research over a period, analyzes the results, and then moves on to another subject or group if needed. Consecutive sampling technique gives the researcher a
chance to work with many topics and fine-tune his/her research by collecting results that have vital insights.

Non-probability sampling examples
Here are three simple examples of non-probability sampling to understand the subject better.
1. An example of convenience sampling would be using student volunteers known to the researcher. Researchers can
send the survey to students belonging to a particular school, college, or university, and act as a sample.
2. In an organization, for studying the career goals of 500 employees, technically, the sample selected should have
proportionate numbers of males and females. Which means there should be 250 males and 250 females. Since this
is unlikely, the researcher selects the groups or strata using quota sampling.
3. Researchers also use this type of sampling to conduct research involving a particular illness in patients or a rare
disease. Researchers can seek help from subjects to refer to other subjects suffering from the same ailment to form
a subjective sample to carry out the study.
 When to use non-probability sampling?
• Use this type of sampling to indicate if a particular trait or characteristic exists in a population.
• Researchers widely use the non-probability sampling method when they aim at conducting qualitative research, pilot
studies, or exploratory research.
• Researchers use it when they have limited time to conduct research or have budget constraints.
• When the researcher needs to observe whether a particular issue needs in-depth analysis, he applies this method.
• Use it when you do not intend to generate results that will generalize the entire population.

Difference between non-probability
sampling and probability sampling
Non-probability sampling Probability sampling
• Sample selection based on the subjective
judgment of the researcher.
• The sample is selected at random.
• Not everyone has an equal chance to
participate.
• Everyone in the population has an equal
chance of getting selected.
• The researcher does not consider sampling
bias.
• Used when sampling bias has to be
reduced.
• Useful when the population has similar
traits.
• Useful when the population is diverse.
• The sample does not accurately represent
the population.
• Used to create an accurate sample.
• Finding respondents is easy. • Finding the right respondents is not easy.

Resource and budget allocation

Resource allocation
 Allocation problems involve the distribution of resources among competing alternatives in
order to minimize total costs or maximize total return. Such problems have the following
components: a set of resources available in given amounts; a set of jobs to be done, each
consuming a specified amount of resources; and a set of costs or returns for each job and
resource. The problem is to determine how much of each resource to allocate to each job.
 If more resources are available than needed, the solution should indicate which resources
are not to be used, taking associated costs into account. Similarly, if there are more jobs than
can be done with available resources, the solution should indicate which jobs are not to be
done, again taking into account the associated costs.
 If each job requires exactly one resource (e.g., one person) and each resource can be used
on only one job, the resulting problem is one of assignment. If resources are divisible, and if
both jobs and resources are expressed in units on the same scale, it is termed a
transportation or distribution problem. If jobs and resources are not expressed in the same
units, it is a general allocation problem.

What Is a Budgetary?
 Budgetary allocations are integral components to an annual
financial plan, or budget, of all organizations. They indicate
the level of resources an organization is committing to a
department or program. Without allocation limits,
expenditures can exceed revenues and result in financial
shortfalls. Anyone working with budgets should understand
how they are used and the limitations they provide.

What is a Budget Allocation?
 A budget is a financial plan used to estimate revenues and
expenditures for a specific period of time. It is a management and
planning tool, not just an accounting document. It assists in the
allocation of resources.
 A budget allocation is the amount of funding designated to each
expenditure line. It designates the maximum amount of funding an
organization is willing to spend on a given item or program, and it
is a limit that is not to be exceeded by the employee authorized to
charge expenses to a particular budget line.

Developing Budgetary Allocations
 Budgets are usually developed for 12-month periods. When developing a budget, revenues
are usually estimated first to determine the level of resources that will be available in the
upcoming budget year. Based on the estimated resources, expenditure limits, also called
budgetary allocations, are assigned to each budget category. When developing budgetary
allocations, all needs of the organization are taken into account and decisions are made
where best to allocate available money.
Budget Category Allocations
 Budgets are usually divided into departments and program units. This allows for easier
identification of the resources allocated to specific programs and functions. Each category
can be made of several budget allocations, referred to as line items, for the specific needs
necessary to support the program or overall department operation.

Budget Allocation and Resource
Planning
 If you or your organisation is preparing a proposal to apply for funds to carry out a project, there are a
number of sections you will have to complete. However, what you do or do not include in the budget
section of your application could be the difference between success and failure. While local funding is
considered to be the most sustainable, focus more on the preparations of a budget as a sustainable
item (insuring funding), and include both local and outside funding sources (as they should never be
limited if needed).
 A budget is defined as patterns of expenditure and revenue over the life of the project. In general, it is a
prediction of the possible costs that will be incurred by carrying out the activities planned in a project.
Realistic planning of finances is key to the implementation of a project or programme. A professional
and transparent approach to budget planning will help convince investors, development banks and
national or international donors to make financial resources available.
 Generally, the budget has mainly two functions. First, it estimates, as realistically as possible, the cost
of completing the objectives identified in the project proposal. The sponsoring agencies will use the
budget details to determine whether the proposal is economically feasible and realistic. Secondly, the
budget provides a means to monitor the project's financial activities over the life of the project. In this
way, it is possible to determine how closely the actual progress toward achieving the objectives is being
made relative to the proposed budget.

How to Start?
 Before drawing up the budget, it is necessary to get an overview
of the type of inputs needed to achieve the objectives of the
project.
Typical categories may be, for example:
people (such as researchers, consultants, other partners’ staff-time)
travel costs (such as bus tickets, meal allowance)
vehicles (such as rental, petrol, driver’s time)
equipment (such as machinery, measuring instruments and other tools)
consumables and supplies (such as material, pumps, bricks or containers)
subcontracts (services and construction work)
 Listing all the categories in columns in a spreadsheet application,
such as Excel, will help you to organise your costs. As the budget
should be in line with the activities set in the work plan, you
should work through the narrative of the proposal identifying all
the costs that must be incurred in order to carry out each single
activity planned. In order to identify systematically the different
expenditures, make sure you list all the activities in the rows of
the same (Excel) table, where you previously defined of the costs
categories.

Further Budget Development
Once you have identified the type of expenditures your project will have, the next step is to classify them according to standard
budget categories. Budget items are generally divided into two classifications: direct costs and indirect costs. According to
the European Commission (EC 2009) “direct costs are all those eligible costs which can be attributed directly to the project and
are identified by the beneficiary as such, in accordance with its accounting principles and its usual internal rules”.
Direct costs can be:
 Personnel costs: They should reflect the total remuneration, including salaries plus social security charges (holiday pay,
pension contribution, health insurance, etc). Usually, the personnel costs are calculated in terms of ‘man days’ or ‘man
months’ of junior, medium and senior grade persons. You will have to identify the productive hours per employee per year to
compute the hourly rate, and these should exclude annual leave, public holidays, weekends and sick leaves.
 Travel and subsistence allowances: First determine what travel expenses the granting agency will allow, and then itemise
the cost of each trip, e.g., round-trip airfare, lodging and meals, taxis, visa, etc. You can plan the reimbursement of the costs
to your employees based on actual costs or a lump sum or per diem payment. This last can be calculated through a simple
addition of the possible costs that one employee might have spending one day (with and without night) outside his/her
residential area.
 Vehicles: Usually, this cost will be included in the travel and subsistence item. You will need to consider the costs of renting
or maintaining a car for the purposes of the project. If you plan to drive your own car, you may claim a certain amount per
mile.
 Durable equipment: Any item which will retain its usefulness beyond the grant period is considered capital equipment.
Funding agencies have different views on the purchase and maintenance of equipment, so be sure you know the policy of
the agency before including such costs in your budget.
 Consumables and supplies: Include enough supply money for all activities in the project. Typical consumables are
stationary, duplicating supplies, typing/computing supplies, and software.

Indirect costs
 Indirect costs are all those eligible costs which cannot be identified by the beneficiary as
being directly attributed to the project, but which can be identified and justified by its
accounting system as being incurred in direct relationship with the eligible direct costs
attributed to the project. Indirect costs, also called overheads, Facilities & Administrative
Costs, typically are costs of operating and maintaining buildings (electricity/gas/water bills),
grounds and equipment, depreciation, general and departmental administrative salaries and
expenses and library costs.
 Rules for determining the overhead in a funding programme is usually given by the donor, so
be sure to find out what percentage, if any, the funding source will allow for indirect costs,
and determine which portion of your budget the percentage applies to. Sometimes indirect
costs are a percentage of the total direct costs, or of the personnel costs, or of the salary and
wages item alone.
 When you are determining the actual rate of the costs related to your action, be as close to
reality as possible. It is important that the budget is compiled in close cooperation with staff
from the financial department, so you would obtain realistic numbers.

Budget tracking/ Monitoring Budgetary
Allocations
 Budget tracking is a possible way forward towards accomplishing the
objectives. Budget tracking is needed to make sure funds from the national
level will reach the right beneficiaries.
 Budgetary allocations should be routinely monitored to ensure the amounts
budgeted are sufficient to meet expenditures. It is important to have a
tracking system in place for all purchase orders and bills. The purchase
orders and bills should be matched regularly against the budgetary allocation
to ensure sufficient funds exist for the remainder of the budget year.

Pilot Testing
 Pilot testing is a rehearsal of your research study, allowing
you to test your research approach with a small number of
test participants before you conduct your main study.
Although this is an additional step, it may be the time best
spent on any research project.
 A pilot study, pilot project, pilot test, or pilot experiment is a
small-scale preliminary study conducted to evaluate
feasibility, duration, cost, adverse events, and improve upon
the study design prior to performance of a full-
scale research project.

 A pilot survey is a strategy used
to test the questionnaire using a smaller sample compared
to the planned sample size. In this phase of conducting
a survey, the questionnaire is administered to a percentage
of the total sample population, or in more informal cases just
to a convenience sample.

Sample Size
 When estimating the sample size for the pilot study, rule to
use at least 30 subjects or minimum sample size of 12
subjects.

Advantages and Disadvantages of Pilot
study
 Advantages include:
• Establishes the validity of research based upon the expert knowledge of other researchers in the discipline,
therefore preventing falsified work from being accepted within an area of study.
• Provides valuable feedback so that researchers can revise and improve their papers before publication.
• Enables journal editors to select the most important research findings for publication in their journals, based upon
the objective, independent reviews of an expert group.
• The process of peer review is understood and accepted by the majority of researchers.
 Disadvantages include:
• It can cause lengthy delays in the dissemination of research findings.
• It is a time consuming process which places considerable demands on the academic community. There has been
extensive debate as to how effective the peer review process really is in detecting errors in academic papers.
• It may be difficult to protect the anonymity of referees in very specialised research fields where there may be only a
small number of experts.
• It is sometimes accused of protecting established opinions and not being open to genuinely new ideas.
• Ultimately it may not prevent the publication of poor research as review standards may be lower in less prestigious
journals.

Data Collection
Data collection is defined as the procedure of collecting,
measuring and analyzing accurate insights for research using
standard validated techniques. A researcher can evaluate their
hypothesis on the basis of collected data. In most cases, data
collection is the primary and most important step for research,
irrespective of the field of research. The approach of data
collection is different for different fields of study, depending on
the required information.

Data Collection Methods: Phone vs.
Online vs. In-Person Interviews
Essentially there are four choices for data collection – in-person interviews, mail, phone
and online. There are pros and cons to each of these modes.
 In-Person Interviews
Pros: In-depth and a high degree of confidence on the data
Cons: Time consuming, expensive and can be dismissed as anecdotal
 Mail Surveys
Pros: Can reach anyone and everyone – no barrier
Cons: Expensive, data collection errors, lag time
 Phone Surveys
Pros: High degree of confidence in the data collected, reach almost anyone
Cons: Expensive, cannot self-administer, need to hire an agency
 Web/Online Surveys
Pros: Cheap, can self-administer, very low probability of data errors
Cons: Not all your customers might have an email address/be on the internet, customers
may be wary of divulging information online.

Analysing and Interpreting Data
 Data analysis and interpretation is the process of assigning
meaning to the collected information and determining the
conclusions, significance, and implications of the findings.
The steps involved in data analysis are a function of the type
of information collected, however, returning to the purpose of
the assessment and the assessment questions will provide a
structure for the organization of the data and a focus for the
analysis.

The analysis of NUMERICAL (QUANTITATIVE) DATA is represented in mathematical terms.
The most common statistical terms include:
• Mean – The mean score represents a numerical average for a set of responses.
• Standard deviation – The standard deviation represents the distribution of the responses
around the mean. It indicates the degree of consistency among the responses. The standard
deviation, in conjunction with the mean, provides a better understanding of the data. For
example, if the mean is 3.3 with a standard deviation (StD) of 0.4, then two-thirds of the
responses lie between 2.9 (3.3 – 0.4) and 3.7 (3.3 + 0.4).
• Frequency distribution – Frequency distribution indicates the frequency of each response.
For example, if respondents answer a question using an agree/disagree scale, the
percentage of respondents who selected each response on the scale would be indicated.
The frequency distribution provides additional information beyond the mean, since it allows
for examining the level of consensus among the data.
 Higher levels of statistical analysis (e.g., t-test, factor analysis, regression, ANOVA) can be
conducted on the data, but these are not frequently used in most program/project
assessments.
 The analysis of NARRATIVE (QUALITATIVE) DATA is conducted by organizing the data into
common themes or categories. It is often more difficult to interpret narrative data since it
lacks the built-in structure found in numerical data. Initially, the narrative data appears to be a
collection of random, unconnected statements. The assessment purpose and questions can

 Focus groups and Interviews:
• Read and organize the data from each question separately. This approach permits focusing
on one question at a time (e.g., experiences with tutoring services, characteristics of tutor,
student responsibility in the tutoring process).
• Group the comments by themes, topics, or categories. This approach allows for focusing on
one area at a time (e.g., characteristics of tutor – level of preparation, knowledge of content
area, availability).
 Documents
• Code content and characteristics of documents into various categories (e.g., training manual
– policies and procedures, communication, responsibilities).
 Observations
• Code patterns from the focus of the observation (e.g., behavioral patterns – amount of time
engaged/not engaged in activity, type of engagement, communication, interpersonal skills).
 The analysis of the data via statistical measures and/or narrative themes should provide
answers to the assessment questions. Interpreting the analyzed data from the appropriate
perspective allows for determination of the significance and implications of the assessment.

Interpreting information
1. Attempt to put the information in perspective, e.g., compare results to what you
expected, promised results; management or program staff; any common
standards for your products or services; original goals (especially if you're
conducting a program evaluation); indications or measures of accomplishing
outcomes or results (especially if you're conducting an outcomes or performance
evaluation); description of the program's experiences, strengths, weaknesses,
etc. (especially if you're conducting a process evaluation).
2. Consider recommendations to help employees improve the program, product or
service; conclusions about program operations or meeting goals, etc.
3. Record conclusions and recommendations in a report, and associate
interpretations to justify your conclusions or recommendations.

Reporting Results
1. The level and scope of content depends on to whom the report is intended, e.g.,
to funders / bankers, employees, clients, customers, the public, etc.
2. Be sure employees have a chance to carefully review and discuss the report.
Translate recommendations to action plans, including who is going to do what
about the research results and by when.
3. Funders / bankers will likely require a report that includes an executive summary
(this is a summary of conclusions and recommendations, not a listing of what
sections of information are in the report -- that's a table of contents); description
of the organization and the program, product, service, etc., under evaluation;
explanation of the research goals, methods, and analysis procedures; listing of
conclusions and recommendations; and any relevant attachments, e.g., inclusion
of research questionnaires, interview guides, etc. The funder may want the
report to be delivered as a presentation, accompanied by an overview of the
report. Or, the funder may want to review the report alone.
4. Be sure to record the research plans and activities in a research plan which can
be referenced when a similar research effort is needed in the future.

Contents of a Research Report --
An Example
Ensure your research plan is documented so that you can regularly and efficiently carry out your research activities. In
your plan, record enough information so that someone outside of the organization can understand what you're
researching and how. For example, consider the following format:
1. Title Page (name of the organization that is being, or has a product/service/program that is being researched; date)
2. Table of Contents
3. Executive Summary (one-page, concise overview of findings and recommendations)
4. Purpose of the Report (what type of research was conducted, what decisions are being aided by the findings of the
research , who is making the decision, etc.)
5. Background About Organization and Product/Service/Program that is being researched
a. Organization Description/History
b. Product/Service/Program Description (that is being researched)
i. Problem Statement (in the case of nonprofits, description of the community need that is being met by the
product/service/program)
ii. Overall Goal(s) of Product/Service/Program
iii. Outcomes (or client/customer impacts) and Performance Measures (that can be measured as indicators
toward the outcomes)
iv. Activities/Technologies of the Product/Service/Program (general description of how the
product/service/program is developed and delivered)
v. Staffing (description of the number of personnel and roles in the organization that are relevant to
developing and delivering the product/service/program)

6. Overall Evaluation Goals (eg, what questions are being answered by the research)
7. Methodology
i. Types of data/information that were collected
ii. How data/information were collected (what instruments were used, etc.)
iii. How data/information were analyzed
iv. Limitations of the evaluation (eg, cautions about findings/conclusions and how to use the
findings/conclusions, etc.)
8. Interpretations and Conclusions (from analysis of the data/information)
9. Recommendations (regarding the decisions that must be made about the product/service/program)
10.Appendices: content of the appendices depends on the goals of the research report, eg.:
i. Instruments used to collect data/information
ii. Data, eg, in tabular format, etc.
iii. Testimonials, comments made by users of the product/service/program
iv. Case studies of users of the product/service/program
v. Any related literature

Contents of Research Report
Preliminary section
 This section mainly consists of identification information for the
study conducted.
 It has the following individual elements:
 Title page: This includes classification data about:
 The target audience, or the intended reader of the report
 The report author(s), including their name, affiliation and address.
 The title of the study presented in a manner to clearly indicate the
study variables;
 Letter of transmittal: This is the letter that goes alongside the
formalized copy of the final report. It broadly refers to the purpose
behind the study
 Letter of authorization: Sometimes the letter of authorization
may be redundant as indications of the formal approval for
conducting the study might be included in the letter of transmittal

 Table of contents: All reports should have a section that clearly indicates the division of the
report based on the formal areas of the study as indicated in the research structure
 Executive summary: This is the last and the most critical element of the preliminary section.
The summary of the entire report, starting from the scope and objectives of the study to the
methodology employed and the results obtained, have to be presented in a brief and concise
manner
 Acknowledgements: A small note acknowledging the contribution of the respondents, the
corporate and the experts who provided inputs for accomplishing the study is to be included
here.
 Main report: This is the most significant and academically robust part of the report. The
sections of this division follow the essential pattern of a typical research study. Problem
definition: This section begins with the formal definition of the research problem. The problem
statement is the research intention and is more or less similar to what was stated earlier as the
title of the research study.
 Study background: Study background presents details of Report Writing the preliminary
conceptualization ofthemanagement decision problem and all the groundwork done in terms of
secondary data analysis, industry experts’ perspectives and any other earlier reporting of
similar approaches undertaken.
 Study scope and objectives: The logical arguments then conclude in the form of definite
statements related to the purpose of the study. A clear definition of the scope and objective of
the study is presented usually after the study background

 Methodology of research:
This section would not be sequentially placed here, for short reports or for a business report.
In such reports, a short description of the methodology followed would be documented in the
appendix
 Interpretations of results and suggested recommendations
The section study results and findings, i.e., the main report, presents a bird’s eye view of the
information asset exists in a summarized and numerical form. This kind of information might
become difficult to understand and convert into actionable steps, thus the real skill of the
researcher lies in simplifying the data in a reader-friendly language.
 Limitations of the study
The last in this section is a brief discussion of the problems encountered during the study
and the constraints in terms of time, financial or human resources.
 End notes The final section of the report provides all the supportive material in the study.
Some of the common details presented in this section are as follows: Appendices: The
appendix section follows the main body of the report and essentially consists of two kinds
of information:
1. Secondary information like long articles or in case the study uses/is based on/refersto
some technical information that needs to be understood by the reader. Or long tables or
articles or legal or policy documents.
2. Primary data that can be compressed and presented in the main body of the report.

 This includes:
 Original questionnaire, discussion guides, formula used for the study,
sample details, original data, long tables and graphs which can be
described in statement form in the text. Bibliography: Thesis an important
part of the final section asset provides the complete details of the
information sources and papers cited in a standardized format. It is
recommended to follow the publication manuals from the American
Psychological Association (APA) or the Harvard method of citation for
preparing this section.
 Footnote: Atypical footnote, as the name indicates, is part of the main
report and comes at the bottom of a page or at the end of the main text.
This could refer to a source that the author has referred to or it may be an
explanation of a particular concept referred to in the text.
 Glossary of terms: In case there are specific terms and technical jargon
used in the report, the researcher should consider putting a glossary in the
form of a word list of terms used in the study. This section is usually the
last section of the report.

Types of Research Reports
1. Classification on the basis of size. Based on the size of the report, it is possible to
divide the report into brief reports and detailed reports.
A Brief reports:
 These kinds of reports are not formally structured and are generally short, sometimes
not running more than four to five pages.
 The information provided has limited scope and is a prelude to the formal structured
report that would subsequently follow.
B Working papers or basic reports
 basic reports are written for the purpose of recording the process carried out in terms of
scope and framework of the study, the methodology followed and instrument designed.
The results and findings would also be recorded here.
 However, the interpretation of the findings and study background might be missing, as
the focus is more on the present study rather than past literature.
C Survey reports might or might not have an academic orientation.
 The focus here is to present findings in easy-to-comprehend format that includes figures
and tables.

2. Classification on the basis of information
 The ways through which the results of the research report can be presented on the
basis of information contained as follows:
A Technical report: A technical report is not written by the researcher himself but is
written on behalf of the researchers.
 In writing technical reports, importance is mainly given to the methods that have
been used to collect the information and the data, the presumptions that were made
and finally, the various presentation techniques that were used to present the
findings and the data.
B Popular report:
 A popular report is formulated when there is a need to draw the conclusions of the
findings of the research report.
 One of the main considerations that should be kept in mind while formulating a
research report is that it must be simple and attractive.
 It must be written in a very simple manner that can be is understood all, and also be
made attractive by using large prints, various sub-headings and by giving cartoons
occasionally.

D Technical reports:
 These are major documents and would include all elements of the basic report, as
well as the interpretations and conclusions, as related to the obtained results.
 This would have a complete problem background and any additional past
data/records that are essential for understanding and interpreting the study results.
 All sources of data, sampling plan, data collection instrument(s), data analysis
outputs would be formally and sequentially documented.
E Business reports:
 These reports include conclusions as understood by the business manager.
 The tables, figures and numbers of the first report would now be pictorially shown
as bar charts and graphs and the reporting tone would be more in business terms.
 Tabular data might be attached in the appendix

3. Classification on the basis of representation
 Following are the ways through which the results of the research report can be classified
on the basis of representation:
A Written report: A written report plays a vital role in every business operation. The manner
in which an organization writes business letters and business reports creates an impression
about its standard.
 Therefore, the organization should emphasize on the improvement of writing skills of the
employees in order to maintain effective relations with their customers.
 Making an effective written report requires a lot of hard work. Therefore, before you begin
writing, it is important to know the objective, i.e., the purpose of writing, collection and
organization of required data.
B Oral report: At times, oral presentation of the results that are drawn out of research is
considered effective, particularly in cases where policy recommendations are to be made.
 This approach proves beneficial because it provides a medium of interaction between the
listeners and the speakers.
 This leads to a better understanding of the findings and their implications.
 However, the main drawback of oral presentation is lack of any permanent records related
to the research.

Steps Involved in Drafting Research Reports
 Step 1: Logical analysis of the subject-matter
 Step 2: Preparation of the final outline
 Step 3: Preparation of the rough draft
 Step 4: Rewriting and polishing Step
 5: Preparation of the final bibliography
 Step 6: Writing the final draft

Principles of a Good Report Writing
 Clear report mandate: While writing the research problem
statement and study background, the writer needs to be
focused, precise and very explicit in terms of the problem
under study, the background that provided the impetus to
conduct the research and the study domain.
 Clearly designed methodology: Any research study has
its unique orientation and scope and thus has a specific and
customized research design, sampling and data collection
plan
 Clear representation of findings: The sample size for
each analysis, any special conditions or data treatment
must be clearly mentioned either as a footnote or as an
endnote, so that the reader takes this into account while
interpreting and understanding the study results.
 Representativeness of study finding: Good research
report is also explicit in terms of extent and scope of the
results obtained, and in terms of the applicability of findings.

Features of a Good Research Report
 Information collected in the report should be relevant and focused
to derive desired results.
 The report should strictly adhere to predefined goals and
objectives.
 The report should provide the description of the questionnaires
used in analysis and the means adopted in their preparation.
 The report should elaborate the methodology used in the
interviews.
 There must be an executive summary of the work in the report.
 The report should not only present the actual analysis but also the
reasons of making this report.
 It should also highlight the advantages and profit it can provide
after successful implementation of business plans described inside
the report.
 It should also mention the methodology of the research presenting
the overall process adopted to create the report.
 The report needs to be flexible enough so that it may be changed
according to requirements.

Criteria for Evaluating Research Reports/Findings
 Clarity:
 The report should be clear in terms of representation of data. It
should be easy to understand.
 Statement of objective:
 The objective of the report should be stated in the beginning of a
report.
 While evaluating, it is important to check whether the research
achieved the stated objective.
 Relevance of data:
 The data of the report should be relevant to the research topic. In
addition, it is important to check whether the recent data was used
in report.
 Analysis of data:
 The data should be properly analyzed. Thus, the evaluator checks
whether all the findings are supported by analysis.
 Unbiased:
 The report should not be biased towards a particular interpretation
because biasness affects the complete process of research.

Research Report: Language Flow and Grammatical
Quality
 All reports must be written in a good language,
using short sentences and correct grammar and
spellings. The main points to be kept in mind in this
light are as follows:
 Context and style:
 Appropriate, informative title for the report
 Crisp, specific, unbiased writing with minimal
jargon
 Adequate analysis of prior relevant research
 Questions/hypotheses:
 Clearly stated questions or hypotheses
 Thorough operational definitions of key concepts
along with the exact wording or measurement of
the key variables

Research Report: Language Flow and Grammatical
Quality
 Research procedures:
 Full and clear description of the research design
 Demographic profile of the participants/subjects
 Specific data gathering procedures
 Data analysis:
 Appropriate inferential statistics for sample or
experimental data and appropriate use of descriptive
statistics
 Clear and reasonable interpretation of the statistical
findings, accompanied by effective tables and figures
 Summary:
 Fair assessment of the implications and limitations of
the findings, effective commentary on the overall
implications of the findings for theory and/or policy

Clarity and Brevity of Expressions
 There is a famous saying that ‘words are like mirror that
reflect the personality of the person from whose mouth
they come out’.
 Thus, if a research wants to absorb the attention of the
reader, then it must have clarity in its expression as this
will also tell a lot about the clarity of the researcher's
thought.
 Experts emphasize the importance of using as few
words as possible to deliver your message.
 However, sometimes messages that are very brief
sacrifice clarity and leave out vital information.
 Thus, while crafting his report, the researcher should
choose clarity over brevity, and include all relevant
information and be sure it is logically organized.

References and Annotations
 Citations and referencing:
 A citation is the acknowledgement in your writing of the work of other
authors and includes paraphrasing and making direct quotes.
 Unless citation is very necessary, you should write the material in
your own words.
 This shows that you understand what you have read and know how
to apply it, to your own context.
 Direct quotes should be used sparingly.
 Direct quotes:
 Short direct quotes: These need to be placed between quotation
marks. For example,Rosenfield defines a cluster as a ‘geographically
bounded concentration of similar, related or complementary
businesses, with active channels for business transactions,
communications and dialogue that share specialized infrastructure,
common opportunities and threats.’
 This shows clearly that the words being used are not your own
words.
 Long direct quotes: There are occasions when it is useful to include
long direct quotes. If you are quoting more than forty words, you
should again use quotation marks but also indent the text.

Data Support and Diagrammatic Elucidation
 For example: The visual representation of the findings in the
form of lines or boxes and bars relative to a number line is
easy to comprehend and interpret. There are some standard
rules and procedures available to the researcher for this; also
there are computer programs like MS Excel and SPSS, where
the numbered data can be converted with ease into graphical
form.
 Line and curve graphs: Usually, when the objective into
demonstrate trends and some sort of pattern in the data, a
line chart is the best option available to the researcher as the
line is able to clearly portray any change in pattern during a
particular time period.
 Area or stratum charts: Area charts are like the line charts,
usually used to Report Writing demonstrate changes in a
pattern over a period of time
 Pie charts: Another way of demonstrating the area or stratum
or sectional representation is through the pie charts. The
critical difference between a line and pie chart is that the pie
chart cannot show changes over time. It simply shows the
cross-section of a single time period.

Data Support and Diagrammatic Elucidation
 Bar charts and histograms: A very useful representation of
quantum or magnitude of different objects on the same
parameter are bar diagrams. The comparative position of
objects becomes very clear.
 Pictogram: pictogram shows graphical representation of
data. Pictograms are most often used in popular and general
read such as in magazines and newspapers, as they are eye-
catching and easy to comprehend by one and all.
 Geographic representation: Geographic or regional maps
related to countries, states, districts, territories can be used as
a base to show occurrence of the studied variable in various
regions or to show comparative analysis about major brands
or industries or minerals

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