Research Design- Elements, types , characteristics

Research Design
• Research design is the overall strategy or blueprint for the
collection, measurement and analysis of data for conducting a
study.
• It outlines what, how, when, and where data will be collected
and analyzed to answer the research question.
• Examples:
– Experimental design
– Quasi-experimental design
– Descriptive design
– Correlational design
– Case study design
– Survey design

Research Design
• “A research design is the arrangement of
conditions for collection and analysis of data in a
manner that aims to combine relevance to the
research purpose with economy in procedure.”
• Research Methods in Social Sciences, 1962, p. 50
• An outline of what the researcher will do from
writing the hypothesis and its operational
implications to the final analysis of data.

Research Design Elements
The essential elements are:
• Accurate purpose statement
• Techniques to be implemented for collecting and
analyzing research
• The method applied for analyzing collected details
• Type of research methodology
• Probable objections to research
• Settings for the research study
• Timeline
• Measurement of analysis

Characteristics of Research Design
• Reliability : The design should yield consistent and repeatable
results when the study is replicated under similar conditions.
• Validity : A good design ensures that the results are valid —
meaning the study truly measures what it is intended to measure.
• Internal validity: Accuracy of cause–effect relationships within
the study.
• External validity: Generalizability of findings to other settings
or populations.

Characteristics of Research Design
• Neutrality refers to the absence of bias in all stages of
the research process — from data collection and analysis
to interpretation and reporting.
• Neutrality in research design ensures that the findings are
credible, unbiased, and based purely on evidence,
thereby enhancing the trustworthiness and scientific
validity of the study.
• Generalization refers to the extent to which the
findings of a research study can be applied or
extended beyond the specific sample or setting used in
the study to a larger population or similar situations.

Types of Research Design
• Research design can be a quantitative or qualitative research with
have extensive components. They can both be used or applied
distinctively or together.
• Quantitative Research Design:
• Uses numbers and statistical analysis to measure variables, identify
relationships, and test hypotheses.
• Qualitative Research Design:
• Focuses on understanding words, observations, and subjective
experiences to gain in-depth insights into a phenomenon.
• Mixed-Methods Design:
• Combines both qualitative and quantitative approaches to provide a
more comprehensive understanding of the research problem.

Quantitative Research design
• A quantitative research design is used to examine the
relationship between variable by using numbers and statistics
to explain and analyze its findings
• Four types of quantitative research design:
• Descriptive design research (observing and describing
phenomena) : As the name implies, it is intended to describe
the present status of an issue or a problem which is analyzed
based on the available data and so does not require hypothesis
to begin with.
• It is a theory-based design method created by gathering,
analyzing, and presenting collected data. This allows a
researcher to provide insights into the why and how of
research. Descriptive design helps others better understand the
need for the research.

• Co relational design research (measuring relationships between
variables): Correlational research is a non-experimental
research technique.
• It helps researchers establish a relationship between two closely
connected variables. There is no assumption while evaluating a
relationship between two other variables, and statistical analysis
techniques calculate the relationship between them. This type of
research requires two different groups.
• A correlation coefficient determines the correlation between two
variables whose values range between -1 and +1. If the correlation
coefficient is towards +1, it indicates a positive relationship between
the variables, and -1 means a negative relationship between the two
variables.

• Experimental design research (establishing cause-
and-effect) : This is a method used to establish a
cause and effect relationship between two variables
or among a group of variables. The independent
variable is manipulated to observe the effect on the
depended variable.
• Social sciences often use it to observe human
behaviour by analyzing two groups. Researchers can
have participants change their actions and study how
the people around them react to understand social
psychology better.

• Quasi-experimental design research: As the
name suggests such an experiment is designed
replicating the true experimental design,
except that it does not use randomized sample
groups.
• Also, it is used when a typical research design
is not practicable.

Qualitative Research design
• Exploratory (investigating a new or understudied topic).
• Qualitative research design is exploratory in nature as it
tries to discover not guess the conclusion.
• It seeks to answer the questions what and how. It is a
process to identify or develop a hypothesis that is further
tested using other techniques.
• The researcher is usually the primary instrument that
formulates the question and interprets the meaning of a data.
• The data used are mostly documented words from interview,
newspapers videos etc.
• More than one type of data is collected during this research,
from the field, where the participants are.

Benefits of Research Design
• Clarity of research objectives and desired outcomes .
• Increased validity and reliability: help to minimize the risk of
bias and helps to control extraneous variables.
• Improved data collection: to ensure that the proper data is
collected and data is collected systematically and consistently.
• Better data analysis: providing meaningful insights and
conclusions.
• Improved communication: ensure the results are clean and
influential within the research team and external stakeholders.
• Efficient use of resources: reducing the risk of waste and
maximizing the impact of the research
• A well-designed research plan is essential for successful research,
providing clear and meaningful insights and ensuring that
resources are practical.

Process of Research Design
• The research design process is a systematic and structured approach to
conducting relaible research. and produces meaningful results.
• Consider your aims and approaches: Determine the research
questions and objectives, and identify the theoretical framework and
methodology for the study.
• Choose a type of Research Design: Select the appropriate research
design, such as experimental, correlational, survey, case study, or
ethnographic, based on the research questions and objectives.
• Identify your population and sampling method: Determine the
target population and sample size, and choose the sampling method,
such as random, stratified random sampling, or convenience sampling.

Process of Research Design
• Choose your data collection methods: Decide on the data
collection methods, such as surveys, interviews, observations, or
experiments, and select the appropriate instruments or tools for
collecting data.
• Plan your data collection procedures: Develop a plan for data
collection, including the timeframe, location, and personnel
involved, and ensure ethical considerations.
• Decide on your data analysis strategies: Select the appropriate
data analysis techniques, such as statistical analysis, content
analysis, or discourse analysis, and plan how to interpret the results.
• The process of research design is a critical step in conducting
research. By following the steps of research design, researchers can
ensure that their study is well-planned, ethical, and rigorous.

Features of Research Design
• (a) the sampling design which deals with the method of
selecting items to be observed for the given study
• (b) the observational design which relates to the conditions
under which the observations are to be made;
• (c) the statistical design which concerns with the question of
how many items are to be observed and how the information
and data gathered are to be analysed; and
• (d) the operational design which deals with the techniques
by which the procedures specified in the sampling, statistical
and observational designs can be carried out.

Essentials of Research Design
(i) It is a plan that specifies the sources and types of information
relevant to the research problem.
(ii) It is a strategy specifying which approach will be used for
gathering and analysing the data.
(iii) It also includes the time and cost budgets since most studies
are done under these two constraints.
In brief, research design must, at least, contain—
(a) a clear statement of the research problem;
(b) procedures and techniques to be used for gathering
information;
(c) the population to be studied; and
(d) methods to be used in processing and analysing data

Factors to be considered in defining research
Design
• A research design appropriate for a particular
research problem, usually involves the consideration
of the following factors:
– (i) the means of obtaining information;
– (ii) the availability and skills of the researcher and
his staff, if any;
– (iii) the objective of the problem to be studied;
– (iv) the nature of the problem to be studied; and
– (v) the availability of time and money for the
research work.

Important concepts of Research Design
• Dependent and Independent Variables
• Variable: A characteristic that can take different quantitative or qualitative
values, like height, age, income.
• Continuous variables: Can take any numerical value, including decimals
(e.g., age).
• Discrete variables: Can only take integer values (e.g., number of children).
• Independent variable: The cause or antecedent that researchers manipulate
or observe (e.g., age, sex, treatment).
• Dependent variable: The effect or outcome that depends on independent
variable(s) (e.g., height, behavioral change).

Professor Fisher -Principles of
Experimental Design
• Replication
• Meaning: Repeating the experiment or treatment on several subjects
or samples to confirm that the results are consistent.
• Purpose:
– To increase the reliability and accuracy of results.
– To estimate experimental error.
– To ensure the findings are generalizable beyond a single test.
• Example: Conducting the same psychological test on multiple
groups to confirm consistent behavior patterns.
• According to the Principle of Replication, the experiment should be
repeated more than once. Thus, each treatment is applied in many
experimental units instead of one. By doing so the statistical
accuracy of the experiments is increased.

Experimental Design
• Randomization
• Meaning: The process of assigning subjects to experimental and
control groups by chance rather than by choice.
• Purpose:
– To eliminate selection bias.
– To ensure that both known and unknown extraneous variables
are evenly distributed.
– To make the results statistically valid.
• Example: Randomly assigning students to receive different
teaching methods to ensure that personal abilities are evenly
distributed.
• This principle indicates that we should design or plan the experiment in such a
way that the variations caused by extraneous factors can all be combined
under the general heading of “chance.”

Experimental Design
• The Principle of Local Control is another important principle
of experimental designs.
• Under it the extraneous factor, the known source of
variability, is made to vary deliberately over as wide a range
as necessary and this needs to be done in such a way that the
variability it causes can be measured and hence eliminated
from the experimental error.
• This means that we should plan the experiment in a manner
that we can perform a two-way analysis of variance, in which
the total variability of the data is divided into three
components attributed to treatments (varieties of rice in our
case), the extraneous factor (soil fertility in our case) and
experimental error.*

Experimental Design
• Local Control (Blocking) : Dividing experimental units into
homogeneous groups or blocks based on similar
characteristics before applying treatments.
• Purpose:
– To control the effect of nuisance variables (variables
that are not of primary interest but may influence the
results).
– To increase the precision of the experiment by reducing
variability.
• Example: Grouping participants by age or gender before
applying a new therapy in a medical study.

Experimental Design
• Control of Variables
• Meaning: Keeping all factors constant except the
independent variable being tested.
• Purpose:
– To establish a cause-and-effect relationship.
– To ensure that changes in the dependent variable are
solely due to the independent variable.
• Example: Keeping the same classroom
environment while testing the effect of different
teaching methods.

Experimental Design
• Precision and Accuracy
• Meaning: Designing the experiment and selecting
instruments and procedures that minimize
measurement errors.
• Purpose:
– To increase the dependability of results.
– To ensure the experiment can detect real differences if
they exist.
• Example: Using standardized questionnaires or
calibrated measuring tools.

Experimental Design
• Validity and Reliability
• Meaning: Ensuring that the experiment actually
measures what it intends to measure (validity) and
that results are consistent across trials (reliability).
• Purpose:
– To make research scientifically credible.
– To ensure findings can be replicated in future
studies.
• Example: Using a validated psychological scale
across multiple samples to measure anxiety.

Experimental Design
• Ethical Considerations
• Meaning: Conducting experiments with fairness,
honesty, and respect for participants.
• Purpose:
– To maintain integrity and social responsibility in
research.
– To protect participants from harm and ensure
informed consent.
• Example: Obtaining ethical clearance and participant
consent before conducting human trials.

Research Design- Elements, types , characteristics

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