5 to on.pptx

Definition of Research
• Comprises of two words, namely 're' and 'search'. Re means again and search means to
find out.
• What are we searching???
 searching for knowledge.
• Why are we searching for knowledge???
 To fill the gap between what is and what ought to be

How to conduct Research????
Step 1: Identify the Problem
Sources of problems:
 Personal experience
 Secondary sources
Examples: (broad problems)
• Shrinkage of chure forest.
• Human wildlife conflict in eastern
Nepal

Step 2: clarify the problems
Examples:
Shrinkage of chure forest.
• Illegal forest resources extraction
from Chure forest.
• Unplanned infra structure
development.
• Encroachment
• Forest fire
• …………. (primary/secondary
sources)

Step 3: Selection of research topic
Examples:
Shrinkage of chure forest.
• Illegal forest resources extraction
from Chure forest.
• Factors of illegal forest resources extraction
• Major forest products extracted illegally
• Spatial patterns of forest resource extraction
• Influencing Factors of Illegal Forest Resources Extraction in the Churia Forest
• Drivers of Illegal Forest Resources Extraction in the Churia Forest
• Determinants of Illegal Forest resources Extraction in the Chure Forest
Topic may be:

Proposal Writing
Influencing Factors of Illegal Forest Resources Extraction in the
Churia Forest
We get funding
If funders criteria meet

Proposal Writing
Topic selection: Influencing Factors of Illegal Forest Resources Extraction in the Churia Forest
Executive summary:
Background/Introduction:
Literature review:
(review of secondary
sources)
• what your project is about
• why the project is worth Doing.
• What is the central research problem?
• How is the topic of your research proposal related to
the problem?
• What kinds of research have been done relevant to a particular topic
• Find out the research gaps
• Demonstrates how the research fits within a field of study
• Justifies the research
Original: Demographic and socio-economic characteristics of the rural community that determine their
dependency on forest resources (plagiarism)
Paraphrase : Socio-economic and demographic features of the village community determines the dependency on
forest resources Hussain et al. (2019)

Proposal Writing
Literature review:
(review of secondary
sources)
• What kinds of research have been done relevant to a particular topic
• Find out the research gaps
• Demonstrates how the research fits within a field of study
• Justifies the research
Original: Demographic and socio-economic characteristics of the rural community that determine their
dependency on forest resources (plagiarism)
Paraphrase : Socio-economic and demographic features of the village community determines the dependency on
forest resources Hussain et al. (2019)
Original: Similarly, there is a positive association between age of household head and forest dependency,
although with decreasing impact after attaining a climax of physical power (Soe et al., 2019).
Paraphrase : Age of the household head is positively correlated with forest dependency Soe et al. (2019).

Problem statement and justification
• Statement of the current issues/situation
• Generally include negative points of the current situation
• Explain why this research matters?
• biophysical fragility,
• Higher deforestation rate
• Higher anthropogenic pressure
• Less no of CF
• Biophysical-socio economic factors of forest dependent peoples is still unidentified. (We can use
secondary sources…………..)
Example: Influencing Factors of Illegal Forest Resources Extraction in the Chure Forest
Therefore, this study will underlines the essential demographic and socio-economic characteristics of rural
livelihood on forest resource-dependent in the study area that explain the factors of forest dependency.

References:
• Hussain, J., Zhou, K., Akbar, M., Raza, G., Ali, S., Hussain, A., ... & Ghulam, A. (2019). Dependence of rural
livelihoods on forest resources in Naltar Valley, a dry temperate mountainous region, Pakistan. Global Ecology and
Conservation, 20, e00765.
• Soe, K. T., & Yeo-Chang, Y. O. U. N. (2019). Perceptions of forest-dependent communities toward
participation in forest conservation: A case study in Bago Yoma, South-Central Myanmar. Forest Policy
and Economics, 100, 129-141.

Research Objectives and Research Questions:
• Just research objectives
• Just research questions What are the factors of illegal extraction of forest resources?
To analyze the factors associated with illegal use of forest resources
• To analyze the socioeconomic factors of local people on
illegal forest resource extraction
• To analyze the demographic factors of local people on
• To analyze the farm characteristics of local people on
What are the factors of
illegal extraction of forest
resources?
• How socioeconomic factors of local people affect illegal
forest resource extraction ?
• How demographic factors of local people affect illegal
forest resource extraction?
• What was the extent of resources use patterns ?
To analyze the demographic and
socio economic factors associated
with illegal use of forest resources
Questions
Questions
Objectives
Objectives

Research Hypothesis:
• Quantitative statement about population
Example: more than 60% people are involve in forest resources
extraction
Village
(1000)
population
Sample (10%)
100
Analyze the result Accept/Reject the hypothesis

• Quantitative statement about population
Level of Illegal timber extraction will significantly differ across a
range
A
population
Sample
Collect the timber extraction data
Accept/Reject the hypothesis
B C D
Analyze the data

• Tentative prediction or explanation of the relationship between two or more variables
• Assumptions / prediction of expected outcomes
• Mostly hypothesis testing is used in quantitative research.

Sampling:
Sampling Design
How many trees are there ?
Suppose area of this forest is 100 ha = 100*10000 m2
500 m2
Total trees in the 5 sample plots = (2+3+1+2+2)= 10
Total area of the sample plots = 5*500 = 2500 m2
Average tree per plot = 10/5 = 2
500m2 = 2 tree
1 m2 =2/500 tree
100ha (1000000) = 2/500∗1000000=2000 trees
Total population of the forest = 2000 tree

Sample: representative portion of the whole population.
Sampling : the process of selecting a part of population
Sample size : the number of people in the selected sample
Sampling frame : complete list of individual or people included in the sample
Sampling technique : it refers to the technique or procedure used to select members of the
sample.
Introduction

 The ratio of sample to the whole population is called sampling intensity
 It is expressed in percentage
Sampling Intensity
Sampling intensity (SI) =
𝑆𝑎𝑚𝑝𝑙𝑒
𝑃𝑜𝑝𝑢𝑙𝑎𝑡𝑖𝑜𝑛
∗ 100
500 m2

• Less time
• Reduced cost
• Better supervision
• Administrative convenience
• Suitable for destructive sampling
Advantages of Sampling

Types of sampling/sampling method/sampling techniques

Data Collection:
• Data can be collected from two sources that are internal and external sources.

Types of Data
• There are the following types of known forms of data

Data Analysis
• Plan of Analysis / Statistical Tools
• Plan of statistical analysis (descriptive parts, different test statistics)
• Parametric or non parametric, univariate or multivariate statistics to be employed
• Specific testing or analysis tools to be used
• Software employed (excels, SPSS, SAS…….)

Expected Outputs
• What you expect to get out of the research.
• It will be a good place to summarize the significance of the work.
Budget
SN Particulars Unit # of Unit Rate
Total
(RS)
Justification
1
Food and
Accommodation
Day*person 30*1
Rs 1000/ person/
day
30,000
Hotel charge,
Breakfast, Lunch and
Dinner

Work plan
Activities
Month (2022)
March Apr May June July Aug Sept
Literature Review
Field Visit
Data Analysis
Draft Report Preparation
Final Report Preparation,
Submission and Dissemination

Abstract
Background: A simple opening sentence
 Increasing human population and limited access to off-farm opportunities in chure range put continuous
pressure on chure forest through illegal forest resource extraction
Aims: One or two sentences giving the purpose of the work.
 Therefore, this study will investigates impact of biophysical characteristics of farm, socio-economic and
demographic characteristics of rural livelihood on illegal extraction of forest resources on chure frorest of
Nepal.
Method/data analysis : One or two sentences explaining what was (or will) be done.
 To better estimate the forest resource used by household, we will interview 400 randomly selected households
using a semi-structured questionnaire.
 The binary logistic regression model will be used to evaluate the potential determinants of illegal forest
resource extraction

Abstract
Results/conclusion: One or two sentences indicating the main findings (or what you hope to accomplish with
the project).
 Findings of the research are expected to be guidelines for management of forest resources in geographically
heterogeneous community with different needs and interests for forest
• Usually do not cite
• Don't use symbol, special characteristics etc
• Avoid duplicating words used in your title.
• Capitalized first letter

Overall
Title
Objectives
Methods
Results

Unit-6: Questionaries development
• Drafting measurement questions/checklists/schedules
• Assembling , Pre- testing and revising instruments
• Test of validity and reliability of instruments
• Finalizing and formatting the instruments

Research instruments
• A Research Instrument is a tool used to collect, measure, and analyze data
related to your research interests.
• A research instrument can include interviews, tests, surveys, or checklists
etc.
• The Research Instrument is usually determined by researcher and is tied to the
study methodology.

Characteristics of a Good Research Instrument
• Valid and reliable
• Based on a conceptual framework
• Must gather data suitable for and relevant to the research topic
• Able to test hypothesis and/or answer proposed research questions under
investigation
• Free of bias and appropriate for the context, culture, and diversity of the study
site
• Contains clear and definite instructions to use the instrument

Questionaries designing process

Drafting measurement questions/checklists/schedules
Open ended questionaries: questions that allow respondents to answer in open text format
Example:
• Do you think community forestry helps to improve livelihood of the forest dependent
people?
• What you think about existing revenue sharing of CFUG?
• What you feel about the restructuring of Forestry organization in federal Nepal?
• What are your suggestions to make more collaboration with CFUG and local
government?

Closed ended questionaries: questions that can only be answered by selecting from a
limited number of options, usually multiple-choice questions with a single-word answer ,
'yes' or 'no', or a rating scale (e.g. from strongly agree to strongly disagree).
Example:
• What is the area of your community forest?
• Are you being the member of CFUG present or previous?
• From your perspectives, which level of government should monitor the CFUG?
a. Federal level b. Provincial level c. local level

Dichotomous question: Belonging to the closed-ended family of questions, dichotomous
questions are ones that only offer two possible answers, which are typically presented to
survey takers in the following format – Yes or No, True or False, Agree or Disagree and
Fair or Unfair.
Example:
• Are local people (CFUG) involved in collection of Satuwa?
a. Yes b. No
• Have you think any change in benefit sharing mechanism within CFUG?
a. Yes b. No

Rating scale/Likert scale question:
Example: What you think on the statement that CFUG is supportive to local governance system
strengthening?
a. Strongly agree b. Agree c. Neutral d. Disagree e. strongly disagree

Assembling , Pre- testing and revising instruments
• The practice of pretesting is highly regarded as an effective technique for improving
validity in qualitative data.
• Pretesting involves simulating the formal data collection process on a small scale to identify
practical problems with regard to data collection instruments, sessions, and methodology.
• The value of pretesting can lead to detecting errors, word ambiguity, as well as discovering
possible flaws in survey measurement variables.
• Pretesting can also provide advance warning about how or why a main research project can
fail.

Assembling , Pre- testing and revising instruments
• A typical pretest in qualitative research involves administering the interview to a group of
individuals that have similar characteristics to the target study population, and in a manner
that replicates how the data collection session will be administered
• Pretesting provides an opportunity to make revisions to study materials and data collection
procedures to ensure that appropriate questions are being
• It is vital that pretests be conducted systematically and include practice for all personnel
who will be engaged in data collection procedures for the eventual main study.

Reliability of instruments
• In research, the term reliability means " repeatability" or "consistency"
• It is the degree to which an assessment tool produces stable and consistent results.
• Reliability is the degree of consistency with which the attributes or variables are measured
by an instrument.
• A test is considered reliable if researcher frequently gets the same reading at different time
interval. Eg. Diameter measurement of tree.
• Reliability is the degree of consistency with which an instrument measures the attribute for
which it is designed to measure.
• Reliability is defined as the ability of an instrument to create reproducible results.

Validity of instruments
• Validity refers to an instrument or test actually testing what it suppose to be testing.
- Treece and Treece
• Validity refers to the degree to which an instrument measures what it suppose to measuring.
- Polit and Hungler.
• Validity is the appropriateness, meaning, fullness and usefulness of the interference made
from the scoring of the instrument.
- American Psychological Foundation.

Types of Validity
FACE VALIDITY: Face validity involves an overall look of an
instrument regarding its appropriateness to measure a particular
attribute or phenomenon.
CONTENT VALIDITY: Content validity is concerned with
scope of coverage of the content area to be measured.
CRITERION VALIDITY: This type of validity is a
relationship between measurements of the instrument with some
other external criteria.
CONSTRUCT VALIDITY : It refers to the extent to which
one instrument correlate with other instrument measure similar
construct.

Unit-7
• Data collection methods
• Questionnaire
• Interview
• Observations
• Discussions
• Participatory methods

Data Collection
• Data collection is one of the most important stages in conducting research.
• Data collection is the process of gathering and measuring information on
variables of interest, in an established systematic fashion that enables one to
answer.
• The data collection component of research is common to all fields of study
including physical and social sciences, humanities, business, etc. While
methods vary by discipline,

Data Collection
• Data: Research data is any information that has been collected, observed, generated or
created to validate original research findings.
• Data are the basic individual item numeric or other information gathered through
observation but in themselves they are devoid of information.
• Types of Data
 Qualitative & quantitative
 Primary & secondary
 Time Series data
 Cross –sectional data
 Panel data

Data Collection
• Quantitative data: Quantitative data refers to any information that can be
quantified, counted or measured, and given a numerical value.
Advantages of quantitative data
• It’s relatively quick and easy to collect and it’s easier to draw conclusions
from.
• When you collect quantitative data, the type of results will tell you which
statistical tests are appropriate to use.
• As a result, interpreting your data and presenting those findings is
straightforward and less open to error and subjectivity.

Data Collection
• Disadvantages of quantitative data
• Quantitative data doesn’t always tell you the full story (no matter what the
perspective).
• With irregular information, it can be inconclusive.
• Focusing solely on numbers, there is a risk of missing larger focus information
that can be beneficial.

Data Collection
• Qualitative data: qualitative data is descriptive, expressed in terms of language rather than
numerical values. This type of data cannot be measured or counted. It refers to the words or labels
used to describe certain characteristics or traits
Advantages of qualitative data
• Qualitative data offers rich, in-depth insights and allows you to explore context.
• It’s great for exploratory purposes.
Disadvantages of qualitative data
• It’s not a statistically representative form of data collection because it relies upon the experience of
the host (who can lose data).
• It can also require multiple data sessions, which can lead to misleading conclusions.

Data Collection
Time series data:
• Data collected at a number of specific points in time is called time series data
• A time series is a set of observations on the values that a variable takes at different times
• A time series data set consists of observations on one or several variables over time
• Example: Temperature, Tree height, diameter growth over different time, Growing stock of
forest……..

Data Collection
Cross-sectional Data
• Cross-section data is collected in a single time period and is characterized by individual
units - people, companies, countries, etc.
• Data which is collected on one or more variables collected at a single point in time.
• A cross sectional data set consists of sample of individuals, households, animals, forest etc.
• Some examples include: comparing two forest data at a single time, collection of
demographic, socio economic and farm characteristics data at a single time.

Data Collection
Panel or Longitudinal Data
• These data combine cross-section and time series data.
• Panel data combines cross-sectional and time series data: the same individuals (persons,
firms, cities, etc.) are observed at several points in time (days, years, before and after
treatment etc.).
• Panel data allows you to control for variables you cannot observe or measure
• Example: Data on 1000 individual tree in four different year
• Data on 400 schools in Morang district since 1990 at 5 years interval

Data Collection
Primary Data
• PRIMARY DATA : Are those which are collected a fresh and for the first time and thus
happen to be original in character and known as Primary data
• Method of data collection:
 Questionnaire
 Interview
 Observations
 Discussions

Data Collection
Questionnaire
• A questionnaire is a research instrument consisting of a series of questions and other
prompts for the purpose of gathering information from respondents."
• A measuring device used to query a population/sample in order to obtain information for
analysis.
Form of questionnaire
 Structured
 Semi structured
 Unstructured

Questionnaire
Structured Questionnaire
• Structured questionnaires are those questionnaires in which there are definite, concrete and
pre-determined questions.
• The questions are presented with exactly the same wording and in the same order to all
respondents.
• Resort is taken to this sort of standardization to ensure that all respondents reply to the same
set of questions
• Structured questionnaires have fixed alternative questions in which responses of the
informants are limited to the stated alternatives

Questionnaire
Structured Questionnaire
• A highly structured questionnaire is one in which all questions and answers are specified
and comments in the respondents own words are held to minimum.
• Example:
i. Do you know about the medicinal plant of Satuwa?
a. Yes b. No
i. Is Satuwa found in Himali community forest?
a. Yes b. No
i. Availability of Satuwa in community forest?
a. Abundant b. moderate c. low*

Questionnaire
Semi-Structured Questionnaire
• Semi-structured questionnaires comprise a mixture of closed and open questions.
• They are commonly used in research where there is a need to accommodate a large
range of different responses from companies.
• The use of semi-structured questionnaires enables a mix of qualitative and
quantitative information to be gathered.
• Researcher will have a list of themes and possibly some key questions to be covered.
• Example: What are the damaged caused by wildlife?, Do you have any knowledge
for conservation of this plant resource in community forest?

Questionnaire
Unstructured Questionnaire
• Unstructured questionnaires are made up of questions that elicit free responses.
• These are guided conversations rather than structured interviews and would often be
referred to as a “topic guide”
• Human wildlife conflict, community forestry users participation, Benefit sharing
mechanisms in community forestry……………….

Questionnaire
Disadvantages
• Low rate of return of the properly filled in questionnaires
• It can be used only when respondents are educated and co- operating.
• It is difficult to know whether willing respondents are truly representative
• There is also the possibility of ambiguous replies or omission of replies altogether to certain
questions
• This method is likely to be the slowest of all
• Respondents may misinterpret a question, thereby limiting the validity of the results

Questionnaire
Advantages
• Low cost even when the universe is large and is widely spread geographically.
• It is free from the bias of the interviewer; answers are in respondents own words.
• Respondents have adequate time to give well thought out answers
• Respondents who are not easily approachable can also be reached conveniently.
• Large samples can be made use of and thus the results can be made more dependable and
reliable.

Questionnaire
Steps in Questionnaire development
1. Decide the information required.
2. Define the target respondents.
3. Choose the method(s) of reaching your target respondents.
4. Decide on question content.
5. Develop the question wording
6. Put questions into a meaningful order and format.
7. Check the length of the questionnaire.
8. Pre-test the questionnaire.
9. Develop the final survey form.

Interview
• Interview is the verbal conversation between two people with the objective of collecting
relevant information for the purpose of research.
• According to McNamara, 1999 :
 Interviews are particularly useful for getting the story behind a participant’s experiences.
 The interviewer can pursue in-depth information around the topic.
 Interviews may be useful as follow-up to certain respondents.
 Interview is the verbal conversation between two people with the objective of collecting
relevant information for the purpose of research.
 A verbal technique for obtaining data direct from the primary source.

Types of interview
i. Personal Interview
ii. Telephone Interview
iii. Focus Group Interview
iv. Depth Interview

Types of interview
i. Personal Interview
 Personal interview is a face to face two way communication between the interviewer and
the respondents.
 Generally the personal interview is carried out in planned manner and is referred as
structured interview.
Advantages
• Information at greater depth
• Flexibility of restructuring the questionnaire
• Non response generally low
Disadvantages
• Samples can controlled more effectively
• Personal information can be obtained
• Expensive method
• Respondent may give bias information
• Take more time when samples are more

Types of interview….
ii. Telephone Interview
 The information is collected from the respondent by asking him questions on the phone is
called as telephone interview.
 The combination of telephone and computer has made this method even more popular.
Advantages
• Faster than other methods
• Cheaper than interview
• No field staff is required
• Wider distribution of sample is possible
Disadvantages
• Little time is given to respondents
• Non suitable for intensive survey
• Bias information may be more
• short and to the point

iii. Focus group Interview
 Focus group interview is an unstructured interview which involves a moderator leading a
discussion between a small group of respondents on a specific topic.
Advantages
• It is comparatively easier to drive or conduct
• It allows to explore topics
• It has high “face validity” (data)
• It has low cost in relation to other
Disadvantages
• The researcher has less control over the data
• The data analysis are more difficult to be done.
• It demands interviewers carefully trained
• It takes effort to assemble the groups

iv. Depth Interview
 Depth interview is nondirective in nature where the respondent is given
freedom to answer within the boundaries of the topic of interest.
 An in-depth interview is a type of interview with an individual that aims to
collect detailed information beyond initial and surface-level answers.
 For this reason, these interviews are often quite long and can involve multiple
interviews with the one participants

Observations method
• Observation method is a method under which data from the field is collected with the help of
observation by the observer or by personally going to the field.
• In the words of P.V Young “Observation may be defined as systematic viewing, coupled with
consideration of seen phenomenon.”
• Types:
i. Structured observation
ii. Unstructured observation
iii. Participant observation
iv. Non-Participant observation
v. Uncontrolled observation
vi. Controlled observation

Observations method
Structured observation:
• When the observation is characterized by a careful definition of the units to be observed, the style
of recording the observed information, standardized conditions of observation and the selection of
related data of observation.
• Example: planned observation of nursery seedling growth in different potting mixture
Unstructured observations;
• An unstructured observation is where you do not plan the observations. You will observe events
and phenomena that you come across by chance.
• When it takes place without the above characteristics.
• Observation of different natural phenomena uncertainty (Eg: while travelling, working,
walking……..)

Observations method
Participants observation:
• "Under participant observation, the researcher attempts to participate fully in the live and
activities of members and thus become a member of their group, organization or
community. This enables the researcher to share their experience by not merely observing
but also feeling it"
• Non-participant Observation: involves observing participants without actively
participating. This option is used to understand a phenomenon by entering the community
or social system involved, while staying separate from the activities being observed

Observations method
Uncontrolled observation:
• Without any control on observer or situation
• observation takes place in natural condition.
• Results reliable
• Controlled Observation:
• When observation is take place according to definite pre arranged plan, with experimental
procedure then it is called controlled observation .i.e observation done in laboratory under
controlled conditions

Observations method
Disadvantages of observations
• It requires more time
• Extensive training is needed
• Advantages of Observation:
• Relatively inexpensive method
• The observation technique can be stopped or begun at any time.
• Information researcher get is current information.

Key Informant's Survey
• An informant is a person who has specialized knowledge and/or expertise about a
particular culture or members of a group is key informant.
• Qualitative, in-depth, flexible interviews with persons who know what is going in the
community, “experts” (knowledgeable) about a topic on which we want to get
information.”
• Note that the key informant interview is usually not about that person herself, but about
the topic on which she has information.

Objective of Key Informant's Survey
• The purpose of Key Informant Interviews is to collect information from a wide range of
people- including community leaders, professionals, or residents-who have first hand
knowledge about the community , and our research topic.
• To get general information about the local community
• These community experts, with their particular knowledge and understanding, can provide
insight on the nature of problems and give recommendations for solution.

Participatory methods of data collection
Participatory Rural Appraisal (PRA)
• PRA is a field information collection technique, in which field workers interact with local
peoples aiming to facilitate local capacity to analyze, plan, resolve conflicts, monitor and
evaluate, and take action according to a local agenda
• The approach aims to incorporate the knowledge and opinions of rural people in the
planning and management of development projects and programs.
• An approach and methods for learning about rural life and conditions from, with and by
rural people. (Chambers 1994)
• Dr. Robert Chamber is the founder of this approach, which emerges in the 1980s.

Focus group discussion
• A focus group discussion involves gathering people from similar backgrounds or
experiences together to discuss a specific topic of interest.
• It is a form of qualitative research where questions are asked about their perceptions
attitudes, beliefs, opinion or ideas.
• In focus group discussion participants are free to talk with other group members; unlike
other research methods it encourages discussions with other participants.
• It generally involves group interviewing in which a small group of usually 8 to 12 people.

Focus group discussion
Advantages:
• Free and open discussion among the respondents
• A focus group is not static.
• This dynamism allows better results in terms of information derived by a focus group.
Disadvantages:
• More expensive to execute than surveys
• Hard to get honest opinions for sensitive topics
• Results are biased

Choosing Participants in Focus group discussion
• Gender: Will men and women feel comfortable discussing this topic in a mixed-gender group?
For example, women might feel uncomfortable discussing reproductive health issues if men are in
the group.
• Age: Will age affect the way that people react to this topic? For example, a young person might
feel uncomfortable talking about his drinking habits if older people from his community are in the
room.
• Hierarchy: Will people of different hierarchical positions be able to discuss this topic equally? For
example, a student might feel uncomfortable discussing her teachers if the school principal is in
the FGD.

Steps in Focus group discussion

Steps in Focus group discussion
• Problem Definition
• Identification of Sample
• Identification of Moderator
• Generation and Pre-testing FGD Schedule
• Opening questions
• Introductory questions
• Transition questions
• Key questions
• Ending question

Before Focus group discussion
• Set up venue (quiet environment) and equipment in advance.
• Recruit the participants for FGD.
• Prepare resources.
• Prepare for introduction and questions.
• Plan to arrive early.
• Assemble recording equipment.

During Focus group discussion
• Welcome the Group.
• Distribute name cards.
• Introduction
• Overview of the purpose and format of the FGD
• Informed consent
• Explain recording methods.
• Set ground rules and norms.
• Ensure proper/comfortable seating arrangement

Unit-8: Data Processing and Analysis
Data Processing:
• After collecting data, the raw data is to be converted into meaningful form. The
process of converting data into meaningful form is called data processing.
• It is the process of correcting, minimizing, simplifying, arranging and transforming of
collected data.
• Data processing mainly involves various manipulation necessary for preparing the
data for analysis.
• The processing could be manual or electronic. It involves editing, categorizing the
open-ended questions, coding, preparation of tables and diagrams, summarization etc.

Stages of Data Processing:
Editing:
• Information gathered during data
collection may be incomplete, contain
errors and lack uniformity.
Example:
 Data collected through questionnaire
and schedules may have many errors
and inconsistencies such as;
 Some answer may not be ticked at
proper places
 Some questions may be left unanswered
 Some questions may be wrongly
answered

Stages of Data Processing:
Editing:
• Data editing is define as the process involving the review and adjustment of collected data.
• It is the process of examining the collected survey data to remove errors and inconsistencies.
• The purpose of editing is to remove errors and to improve the quality of the collected data.
Types of Data Editing:
Field Editing
In this type, the researcher may go through the questionnaire as soon as it is filled by respondents to find out
whether or not there is a need for completing partial or connecting vague answers.
Central Editing
Such type of editing relates to the time when all data collection process has been completed. Here a single or
common editor corrects the errors like entry in the wrong place, entry in wrong unit e.t.c. As a rule all the wrong
answers should be dropped from the final results

Coding
• In coding, a particular numeral or symbol is assigned to the answers in order to put the responses in
some definite categories or classes.
• It is the process of converting qualitative data into quantitative data.
• Coding is translating response choices of a questionnaire into numerical values.
• In coding, numbers are assigned to the qualitative attributes of variables to facilitate data entry and
analysis
• Coding enables efficient and effective analysis as the responses are categorized into meaningful
classes.
• Coding decisions are considered while developing or designing the questionnaire or any other data
collection tool.
• Coding can be done manually or through computer.

Types of Coding
pre-coding
• It is the process of assigning codes before going into the field.
• Coding is done at the time of construction of questionnaire or after it is
constructed but before going into the field for survey.
Post-coding;
• It is the process of assigning codes after data collection.
• Here, the coding is done after completing the data collection process of
the survey

Classification of data
• Classification of the data implies that the collected raw data is categorized into common
group having common feature.
• Data having common characteristics are placed in a common group.
• The entire data collected is categorized into various groups or classes, which convey a
meaning to the researcher.
• Classification is done in two ways:
1. Classification according to attributes.
2. Classification according to the class intervals.

Classification of data
CLASSIFICATION ACCORDING THE ATTRIBUTES
• Here the data is classified on the basis of common characteristics that can be descriptive like
literacy, sex, honesty, marital status etc.
• Descriptive features are qualitative in nature and cannot be measured quantitatively but are kindly
considered while making an analysis.
CLASSIFICATION ON THE BASIS OF INTERVAL
• The numerical feature of data can be measured quantitatively and analyzed with the help of some
statistical unit like the data relating to income, production, age, weight etc. come under this
category.
• This type of data is known as statistics of variables and the data is classified by way of intervals.

Tabulation of data
• Tabulation is an orderly arrangement of data in rows and columns.
• Tabulation summarizes the raw data and displays data in form of some statistical tables.
• After editing, coding and classification, the data are put together in some kinds of tables.
• Tabulation is a systematic & logical presentation of data in rows and columns to facilitate
comparison and statistical analysis
• Table can be prepared manually or by computers.

Graphing
• Visual representation of data
• Data are presented as absolute numbers or percentages
• The most informative are simple and self-explanatory
Examples:
 Bar chart
 Pie chart
 Line graph
 Histogram
 Polygon / ogive

Data Entry
• After responses have been coded, they can be entered into data base.
• Raw data can be entered through any software program.
• For example: SPSS, Ms Excel etc.

Data Analysis
• Analysis, particularly in case of survey or experimental data, involves estimating
the values of unknown parameters of the population and testing of hypotheses for
drawing inferences. Analysis may, therefore, be categorized as descriptive analysis
and inferential analysis (Inferential analysis is often known as statistical analysis).
• Data analysis is the process of cleaning, changing, and processing raw data, and
extracting actionable, relevant information, that helps informed decisions.

Data Analysis
Analysis of Data
Descriptive analysis Inferential or statistical
analysis
• Collecting, summarizing and describing data
• Drawing conclusions and/or making decisions
concerning a population based only on sample data

Descriptive Statistics
i. Frequency table
ii. Central tendency
(mean, median, mode)
iii. Diagrams (Bar charts,
pie charts, histograms)
iv. Dispersion (Range,
mean deviation, standard
deviation)
i. Simple correlation
ii. Simple regression i. Multi correlation
ii. Multi regression

Inferential Statistics
 Techniques that allow us to make inferences about a population based on data that we
gather from a sample
 Inferential statistics are used to draw conclusions about a population by examining the
sample
 Study results will vary from sample to sample strictly due to random chance (i.e.,
sampling error)
 Inferential statistics allow us to determine how likely it is to obtain a set of results
from a single sample
 This is also known as testing for “statistical significance”

Estimation
Point estimate: single numerical value used to estimate an unknown population parameter.
Interval Estimate:
• Range of vales used to estimate an unknown population parameter. Interval estimates of
population parameters are called confidence interval.

Hypothesis Testing
Mid-hills
Terai
Objectives: To compare the tree disease in sal forest of terai and mid hills of Nepal
Hypothesis: H0: There is no significant differences of tree disease in terai and mid hills sal forest

Hypothesis Testing
Mid-hills
Terai
Sample Sample
Terai
Mid-hills
20% diseased 25% diseased
Tell me which geographic region is best
suited for the sal forest?

Hypothesis Testing
Sample Sample
Terai
Mid-hills
We can not confidently said that
terai sal forest is less infected .
terai sal forest is less infected .
• Age of the forest
• Silvicultural treatment
• Biophysical factors
May
influence
the disease
Randomization (variation)
Sample size
Unbiased result

Hypothesis Testing
Sample Sample
Terai
Mid-hills
terai region is best suited for sal forest.
Randomization (variation)
We can not confidently conclude
the above result because it might
be because of chance or random
factors
We need confidence level or
Level of significance

Parametric & Non parametric test

Interpretation of findings
 Interpretation refers to the task of drawing inferences from the collected facts after an
analytical and or experimental study.
 In fact, it is a search for broader meaning of research findings.
 The task of interpretation has two major aspects viz.,
 the effort to establish continuity in research through linking the results of a given
study with those of another, and the establishment of some explanation concepts.
 Thus, interpenetration is the device through which the factors that seem to explain what has
been observed by researcher in the course of the study can be better understood and it also
provides a theoretical conception which can serve as a guide for further researches.

Discussion of findings
 The discussion section is essentially written for the sake of explaining your findings
 In very simple terms, what you did to answer the research questions and why you did it that
way
 It explains the results of your study, and connects the results to each research question.
Approaches:
1) Explain your findings
2) Compare the findings
3) Evaluate the findings
4) Infer from the findings

Discussion ………..
1) Explain your findings & Compare
• Give reasons or explanation for the findings
• Explain the scenario during the data collection period which might have some influences on
the results of the research
• Explain the results based on the limitation or constraints during the data collection period
Example: own landholding and distance to the forest had a negative association with forest resource
dependency, indicating that households located far from the forest and have more own landholding
are less inclined to collect forest resources. Results are alike with the results of (Ali and Rahut,
2018). The possible reason would be that the household near the forest is likely to depend on more
forest products.

2) Evaluate the result
• provide assessment of the findings
• decide if the results is negative or positive, successful or otherwise
Example: According to our estimation, among the various forest resources, firewood contributes the
highest share in forest income amounted to 52%. On the other hand, the observed negative
relationship between agriculture income, livestock income, off-farm income, distance to forest, own
landholding and forest dependency provides a supportive insight. Thus, the results confirm that off-
farm income, agriculture income and livestock income will reduce forest dependency.

Example: In summary, government organizations should create new jobs opportunities to improve
the socioeconomic conditions of the local communities to reduce their dependency on natural
resources of the area so the situation may be transformed in sustainable resource use. Finally, the
overall priority policy recommendation is the creation of awareness about the natural resources
conservations amongst all stakeholders followed by a wide-ranging participatory natural resource
management and development policy.

Unit-9: Writing a Research Report
Research Report
• A research report is a completed study that reports an investigation or exploration of a
problem, identifies questions to be addressed, and includes data collected, analyzed,
and interpreted by the researcher.
• Research report is a condensed form or a brief description of the research work done
by the researcher. It involves several steps to present the report in the form of thesis or
dissertation.
• Research report is a medium to communicate research work with relevant people

Characteristics of a Good Report
1. Simplicity
The language shall be as simple as possible so that a report is easily understandable. Jargons and
technical words should be avoided. Even in a technical report there shall be restricted use of technical
terms if it has to be presented to laymen.
2. Clarity:
The language shall be lucid and straight, clearly expressing what is intended to be expressed. For that
the report has to be written in correct form and following correct steps.
3. Brevity:
A report shall not be unnecessarily long so that the patience of the reader is not lost and there is no
confusion of ideas. But, at the same time, a report must be complete. A report is not an essay.
4. Positivity:
As far as possible positive statements should be made instead of negative ones. For example, it is
better to say what should be done and not what should not be done.

5. Punctuation:
Punctuations have to be carefully and correctly used otherwise the meaning of sentences may be
misunderstood or misrepresented.
6. Approach:
There are two types of approaches: (a) Person—When a report is written based on personal
enquiry or observations, the approach shall be personal and the sentences shall be in the first
person and in direct speech, (b) Impersonal—When a report is prepared as a source of
information and when it is merely factual (e.g. a report on a meeting), the approach shall be
impersonal and the sentences shall be in the third person and in indirect speech.

7. Readability:
The keynote of a report is readability. The style of presentation and the diction (use of words) shall be
such that the readers find it attractive and he is compelled to read the report from the beginning to the
end.’ Then only a report serves its purpose. A report on the same subject matter can be written
differently for different classes of readers.
8. Accuracy:
A report shall be accurate when facts are stated in it. It shall not be biased with personal feelings of the
writer.
9. Logical Sequence:
The points in a report shall be arranged with a logical sequence, step by step and not in a haphazard
manner. A planning is necessary before a report is prepared.

10. Proper Form:
A report must be in the proper form. Sometimes there are statutory forms to follow.
11. Presentation:
A report needs an attractive presentation. It depends on the quality of typing or printing as well
as quality of paper used. Big companies make very attractive and colourful Annual Reports.

Procedure of Research Report Writing
Researchers can prepare report at their ease as there are no such set rules or procedure of
writing reports. However, following general guidelines can help for writing research reports:
1. Revising expectation
Before starting report writing, researcher should revisit the purpose of research and expectation
from the researcher. If the researcher is intended to submit academic reports, minimum steps
and format are well designed. So, researcher should identify the answer of some questions as
what is the objective of research? Is there any format of reports? Is there word limit? Who will
read the report? What is the process of report evaluation? etc.

2. Preparing outline
On the basis of nature of data, objective of research, and requirement of the evaluating agency,
researcher need to prepare outline i.e. roadmap to the research report. This helps to decide in
how many chapters, in how many topics, whether descriptive or analytical report is required to
prepare. In simple words, outline helps to arrange the idea before starting write up.
3. Arranging data
On the basis of objectives, population and sample for the research, researcher collects the data
from different sources. Different types of data are collected for the purpose. Such different data
from different sources need to be processed and tabulated. Only relevant data are sequentially
arranged so that right information will be obtained at the right time for the right purpose.

4. Start writing
Now, researcher should start writing the report. Report should started within introduction and proceed
with the content and topic arranged on the outline.
5. Preparing the first draft
The report completed with a single effort may not be excellent. Thus, researcher should update and
upgrade the report with series of revisions. For this purpose, the first draft is to be prepared and revisit
the whole draft carefully.
6. Review and rewrite
Every report consists of scope of some improvement. It is true that in each reading, you can find
something to rewrite or rearrange.

Types of Research Report
"Research report can vary differently in its length, type and purpose. Kerlinger (2004) states
that the results of a research investigation can be presented in number of ways via a technical
report, a popular report, a monograph or at times even in the form of oral presentation.
i. Long Report and Short Report
ii. Internal and External Report
iii. Vertical and Lateral Report
iv. Periodic Report
v. Formal and Informal Reports
vi. Proposal Report
vii. Functional Report
viii. Descriptive Report
ix. Analytical Report
x. Technical Report
xi. Popular Report:

i. Long Report and Short Report:
ii. Internal and External Report
iii. Vertical and Lateral Report
iv. Periodic Report
v. Formal and Informal Reports
vi. Proposal Report
vii. Functional Report
viii. Descriptive Report
ix. Analytical Report
x. Technical Report
xi. Popular Report:

i. Short Report:
• Usually shorter reports begin directly with conclusions and recommendations.
• Short reports are informal in nature.
• It is written for routine and recurring problems.
• Short report writing is usually completed in a page or two. As the name implies, a short report is very short in
length.
i. Long Report:
• Long report begins with prefatory contents highlighting the problem statement, objectives, scope, methods
followed
• In a long report, the writing style is formal and impersonal.
• A Long report is suitable for Complex and non-recurring problems.
• A long report is not at all possible to be completed in a page or two

Internal and External Report:
• An internal report stays within a certain organization or group of people. In the case of office
settings, internal reports are for within the organization.
• We prepare external reports, such as a news report in the newspaper about an incident or the annual
reports of companies for distribution outside the organization. We call these as public reports
Vertical and Lateral Report
• This is about the hierarchy of the reports’ ultimate target. If the report is for your management or for
your mentees, it’s a vertical report. Wherever a direction of upwards or downwards comes into
motion, we call it a vertical report.
• Lateral reports, on the other hand, assist in coordination in the organization. A report traveling
between units of the same organization level (for example, a report among the administration and
finance departments) is later.

Periodic Report:
• Periodic reports are sent out on regularly pre-scheduled dates.
• Example; annual reports, Government mandate to be periodic in nature.
• That is why we have annual or quarterly or half-yearly reports.
Informational Report
• Informational reports (attendance reports, annual budget reports, monthly financial reports, and
such) carry objective information from one area of an organization to maybe a larger system

Proposal Report:
• These kinds of reports are like an extension to the analytical/problem-solving reports. A proposal is a
document one prepares to describe how one organization can provide a solution to a problem they
are facing.
Descriptive Report:
• In descriptive report, researcher describes the facts, trends or opinions experienced or gathered
during the research work. In such reports, data presentation and analysis are more importantly
presented. Such reports are more suitable in case of describing current situations, etc. It is more
popular method of report writing.

Analytical Report:
As name given analytical, such reports are prepared with analyzing and interpretation of the facts or
trends or situations. This means analytical report is one step ahead than descriptive reports. Such reports
follow the scientific investigation and reporting.
Technical Report:
the technical report the main emphasis is on
i. the methods employed,
ii. assumptions made in the course of the study,
iii. the detailed presentation of the findings including their limitations and supporting data.

A general outline of a technical report can be as follows:
1. Summary of results: A brief review of the main findings just in two or three pages.
2. Nature of the study: Description of the general objectives of study, formulation of the problem in operational terms,
the working hypothesis, the type of analysis and data required, etc.
3. Methods employed: Specific methods used in the study and their limitations. For instance, in sampling studies we
should give details of sample design viz., sample size, sample selection, etc.
4. Data: Discussion of data collected, their sources, characteristics and limitations. If secondary data are used, their
suitability to the problem at hand be fully assessed. In case of a survey, the manner in which data were collected should
be fully described.
5. Analysis of data and presentation of findings: The analysis of data and presentation of the findings of the study
with supporting data in the form of tables and charts be fully narrated. This, in fact, happens to be the main body of the
report usually extending over several chapters.
6. Conclusions: A detailed summary of the findings and the policy implications drawn from the results be explained.
7. Bibliography: Bibliography of various sources consulted be prepared and attached.

Popular Report:
The popular report is one which gives emphasis on simplicity and attractiveness. The simplification
should be sought through clear writing, minimization of technical, particularly mathematical, details
and liberal use of charts and diagrams. Attractive layout along with large print, many subheadings, even
an occasional cartoon now and then is another characteristic feature of the popular report. Besides, in
such a report emphasis is given on practical aspects and policy implications. We give below a general
outline of a popular report.

Basic elements of Research Report
There is no one best format for all reports. Format depends on
several relevant variables. One must employ a suitable format to
create desirable impression with clarity. Report must be attractive.
It should be written systematically and bound carefully. A report
must use the format (often called structure) that best fit the needs
and wants of its readers. Normally, following format is suggested
as a basic outline, which has sufficient flexibly to meet the most
situations.

Research report is divided into three parts as:
I. First Part (Formality Part):
(i) Cover page
(ii) Title page
(iii) Certificate or statement
(iv) Index (brief contents)
(v) Table of contents (detailed index)
(vi) Acknowledgement
(vii) List of tables and figures used
(viii) Preface/forwarding/introduction
(ix) Summary report

II. Main Report (Central Part of Report):
(i) Statement of objectives
(ii) Methodology and research design
(iii) Types of data and its sources
(iv) Sampling decisions
(v) Data collection methods
(vi) Data collection tools
(vii) Fieldwork
(viii) Analysis and interpretation (including tables, charts, figures, etc.)
(ix) Findings
(x) Limitations
(xi) Conclusions and recommendations
(xii) Any other relevant detail

III. Appendix (Additional Details):
(i) Copies of forms used
(ii) Tables not included in findings
(iii) A copy of questionnaire
(iv) Detail of sampling and rate of response
(v) Statement of expenses
(vi) Bibliography – list of books, magazines, journals, and other reports
(vii) Any other relevant information

Scientific articles
Scientific research articles provide a method for scientists to communicate with other scientists about
the results of their research.
The true value of any research is only realized when the results are subject to peer review and then
published in journals

Format of Scientific articles
A standard format is used for these articles, in which the author presents the research in an orderly, logical
manner. This format is:
Title
Authors
Abstract
Introduction
Materials and Methods
Results (with Tables and Figures)
Discussion
Acknowledgments
Reference(Literature Cited)

Research Ethics
• According to Oxford Dictionary, Ethics are moral principles that govern a person's
behavior or the conducting of an activity.
• Research ethics is specifically interested in the analysis of ethical issues that are raised
when people (or even animals) are involved as participants in research.
• Research ethics provides guidelines for the responsible conduct of research.
• It educates and monitors researchers conducting research to ensure a high ethical
standard.
• Research ethics is closely related to the ethical principles of social responsibility.
• Research ethics provides guidelines for the responsible conduct of research. In addition,
it educates and monitors scientists conducting research to ensure a high ethical standard.

Research ethical guidelines and principals
• Honesty in reporting data, results, methods, procedures, and publication status.
• Objectivity to avoid bias in experimental design, data analysis, interpretation, and peer
review.
• Integrity, acting with sincerity, striving for consistency of thought and action.
• Carefulness to avoid careless errors and negligence; proper documentation of all aspects.
• Openness in sharing data, results, ideas, tools, resources and openness to criticisms and
new ideas
• Respect for intellectual property rights such as patents, copyrights, and other forms of
intellectual property.
• Confidentiality in context of communications, personal records, and privacy issues.

• Responsible publication with an aim to serve the society. avoiding wasteful and
duplicative publication.
• Responsible mentoring in terms of guiding research students
• Ensuring legality of the whole process by obeying relevant laws, that is, institutional and
governmental policies.
• Animal care through proper experimental design.
• Respect the nature.

Honesty:
Honestly report data, results, methods and procedures, and publication status. Do not fabricate, falsify, or
misrepresent data.
Objectivity:
Strive to avoid bias in experimental design, data analysis, data interpretation, peer review, personnel
decisions, and other aspects of research.
Integrity:
Keep your promises and agreements; act with sincerity; strive for consistency of thought and action.
Carefulness:
Avoid careless errors and negligence; carefully and critically examine your own work and the work of
your peers. Keep good records of research activities.
Openness:
Share data, results, ideas, tools, resources. Be open to criticism and new ideas.

Respect for Intellectual Property:
Honor patents, copyrights, and other forms of intellectual property. Do not use unpublished data, methods,
or results without permission. Give credit where credit is due. Never plagiarize.
Confidentiality:
Protect confidential communications, such as papers or grants submitted for publication, personnel records,
trade or military secrets, and patient records.
Responsible Publication:
Publish in order to advance research and scholarship, not to advance just your own career. Avoid wasteful
and duplicative publication.
Responsible Mentoring:
Help to educate, mentor, and advise students. Promote their welfare and allow them to make their own
decisions.
Respect for Colleagues:
Respect your colleagues and treat them fairly.

Social Responsibility:
Strive to promote social good and prevent or mitigate social harms through research, public education, and
advocacy.
Non-Discrimination:
Avoid discrimination against colleagues or students on the basis of sex, race, ethnicity, or other factors that
are not related to their scientific competence and integrity.
Competence:
Maintain and improve your own professional competence and expertise through lifelong education and
learning; take steps to promote competence in science as a whole.
Legality:
Know and obey relevant laws and institutional and governmental policies.
Animal Care:
Show proper respect and care for animals when using them in research.

It helps in promoting the aims and objectives of research.
It promotes the values that are essential to collaborative work and collaboration, such as trust, accountability,
mutual respect, and fairness.
It hods the researcher accountable to the public and society.
It helps in building public support for research, which in return can help in getting participants who take part
in the research willingly.
To promote aim of research i.e expansinon of knowledge.
To support the value require for the collaborative work.
To protect data, anonymity of the subjects, and confidentiality, and the ability to build trust-based
relationship with the respondents and retain it.
To protect research participant's right and welfare, and reduce the risk o physical and psychological
discomfort, damage, and/or threats appearing because of research procedures.
To get the funds and publish your work in reputed journal.

Importance of research ethics
• It helps in promoting the aims and objectives of research.
• It promotes the values that are essential to collaborative work and collaboration, such as trust,
accountability, mutual respect, and fairness.
• It hods the researcher accountable to the public and society.
• It helps in building public support for research, which in return can help in getting participants who take
part in the research willingly.
• To promote aim of research i.e expansion of knowledge.
• To protect data, secrecy of the subjects, and confidentiality, and the ability to build trust-based
relationship with the respondents and retain it.
• To protect research participant's right and welfare, and reduce the risk of physical and psychological
discomfort, damage, and/or threats appearing because of research procedures.
• To get the funds and publish your work in reputed journal.

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