This document summarizes a presentation by Dr. K. Prabhakar on research methods. The objectives are to understand the research process, key definitions, and how to apply the concepts to economics or other social sciences. The presentation covers ontology, or what exists in the world; epistemology, or the nature of knowledge; and methodology, or how to conduct research. Examples are given of different perspectives within ontology, epistemology and methodology, such as realist vs. constructivist views of knowledge. Key aspects of research design are also discussed, including hypotheses generation and testing. Post-Keynesian economics is provided as an example research approach.
One question that always works in the mind of the research scholar is what are the likely questions by examiners for evaluation as well a viva. Here are some guidelines.
This presentation is provide introduction to research design with focus on distinction between different strategies' of Research. Especially qualitative, quantitative and mixed methods. .
Introduction to writing research questions and determining what variables to use. Introductory concepts for school personnel interested in action research.
One question that always works in the mind of the research scholar is what are the likely questions by examiners for evaluation as well a viva. Here are some guidelines.
This presentation is provide introduction to research design with focus on distinction between different strategies' of Research. Especially qualitative, quantitative and mixed methods. .
Introduction to writing research questions and determining what variables to use. Introductory concepts for school personnel interested in action research.
Process to develop your research question and the elements of a good research question are discussed. Scripts to write it are presented so you can apply them to your own case and criteria to evaluate your work included.
A research paper writing is a problem for every newcomer in the research field. This slide deck explains research writing in simple words and examples.
How to study any publication deeply for analysis and research. The process and reporting format are presented with examples. This paves way for incremental discovery and innovation and validation / consolidation.
Presentation deals with scientific process of Hypothesis formulation. Presentation would quench the thirst of beginners in social sciences researchers especially in commerce and Management towards basic understanding of Research Issues, Statement of Research Problem formulating hypothesis and research protocol. Presentation attempts to simplify process of narrowing the research problem from research issue and helps to formulate hypothesis scientifically. Deciding on appropriate title to research is equally important, this presentation discusses different context which helps to decide on appropriate title. Presentation includes case study examples for sound understanding.
Writing a research proposal is a very important step for research at any level. Good quality research is always based on a perfectly planned outline. The meaning & the procedure of writing a research proposal is described in the given presentation.
Process to develop your research question and the elements of a good research question are discussed. Scripts to write it are presented so you can apply them to your own case and criteria to evaluate your work included.
A research paper writing is a problem for every newcomer in the research field. This slide deck explains research writing in simple words and examples.
How to study any publication deeply for analysis and research. The process and reporting format are presented with examples. This paves way for incremental discovery and innovation and validation / consolidation.
Presentation deals with scientific process of Hypothesis formulation. Presentation would quench the thirst of beginners in social sciences researchers especially in commerce and Management towards basic understanding of Research Issues, Statement of Research Problem formulating hypothesis and research protocol. Presentation attempts to simplify process of narrowing the research problem from research issue and helps to formulate hypothesis scientifically. Deciding on appropriate title to research is equally important, this presentation discusses different context which helps to decide on appropriate title. Presentation includes case study examples for sound understanding.
Writing a research proposal is a very important step for research at any level. Good quality research is always based on a perfectly planned outline. The meaning & the procedure of writing a research proposal is described in the given presentation.
HI6008 Business Research Lecture 01(1) (1).pptxabeerarif
Assignment 3 Reflective writing aims to get you to think
about your learning and understand your learning experiences.Evaluate the effectiveness and your usefulness of the learning experience
Make judgements that are clearly connected to observations you have made.
Answer the questions:
− What is your opinion about learning experience?
− What is the value of this experience?
2. Explain how this learning process will be useful to you
Consider: In what ways might this learning experience serve you in:course
− program
− future career
− life generally
Answer the question: ‘How you will transfer or apply your new knowledge and
insights in the future?’
3. Describe objectively what happened in the learning process
Give the details of what happened in the learning process. Answer the question:
‘What you did, read, see, and hear?
4. Evaluate what you learn
Make judgments connected to observations you have made in the Business
Research. Answer the question: ‘How Business Research was useful for your
Research Learning Process?’
5. Explain your learning process:
1.The main purpose of this presentation is to share some of the major aspects of considering management research as a practically- oriented social science in terms of its similarities to, and differences from , the other social sciences and the natural sciences.
2.to explore the implications of it being a practically-oriented type of knowledge producing activity.
3.to share its position as a social science in relation to other sciences and scientific knowledge in general through a discussion of three major points in the 'naturalism' debate.
These slides are for teachers and researchers to know how to address student-centered learning
Inclusive learning
Critical thinking , these three dimensions are addressed in the slides. Please do share your thoughts.
What is the significance of p value while reporting statistical analysis. Is there an alternate approach for Fisher, if so what is that approach. These are some of the issues addressed here.
This presentation will address the issue of sample size determination for social sciences. A simple example is provided for every to understand and explain the sample size determination.
Here different concepts you come across in the research methodology are discussed. It is applicable to social sciences to a large extent. The definitions are explained in a way that will be understood by social scientists.
This lecture will help Research scholars at the starting of their research issues regarding definitions of variables, what is theory and creating a sapling map..
This presentation is for Chartered Accountants on Web 2.0. It discusses the opportunities offered by social media. Risk and management of risk of social media is discussed.
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Empowering the Data Analytics Ecosystem: A Laser Focus on Value
The data analytics ecosystem thrives when every component functions at its peak, unlocking the true potential of data. Here's a laser focus on key areas for an empowered ecosystem:
1. Democratize Access, Not Data:
Granular Access Controls: Provide users with self-service tools tailored to their specific needs, preventing data overload and misuse.
Data Catalogs: Implement robust data catalogs for easy discovery and understanding of available data sources.
2. Foster Collaboration with Clear Roles:
Data Mesh Architecture: Break down data silos by creating a distributed data ownership model with clear ownership and responsibilities.
Collaborative Workspaces: Utilize interactive platforms where data scientists, analysts, and domain experts can work seamlessly together.
3. Leverage Advanced Analytics Strategically:
AI-powered Automation: Automate repetitive tasks like data cleaning and feature engineering, freeing up data talent for higher-level analysis.
Right-Tool Selection: Strategically choose the most effective advanced analytics techniques (e.g., AI, ML) based on specific business problems.
4. Prioritize Data Quality with Automation:
Automated Data Validation: Implement automated data quality checks to identify and rectify errors at the source, minimizing downstream issues.
Data Lineage Tracking: Track the flow of data throughout the ecosystem, ensuring transparency and facilitating root cause analysis for errors.
5. Cultivate a Data-Driven Mindset:
Metrics-Driven Performance Management: Align KPIs and performance metrics with data-driven insights to ensure actionable decision making.
Data Storytelling Workshops: Equip stakeholders with the skills to translate complex data findings into compelling narratives that drive action.
Benefits of a Precise Ecosystem:
Sharpened Focus: Precise access and clear roles ensure everyone works with the most relevant data, maximizing efficiency.
Actionable Insights: Strategic analytics and automated quality checks lead to more reliable and actionable data insights.
Continuous Improvement: Data-driven performance management fosters a culture of learning and continuous improvement.
Sustainable Growth: Empowered by data, organizations can make informed decisions to drive sustainable growth and innovation.
By focusing on these precise actions, organizations can create an empowered data analytics ecosystem that delivers real value by driving data-driven decisions and maximizing the return on their data investment.
Opendatabay - Open Data Marketplace.pptxOpendatabay
Opendatabay.com unlocks the power of data for everyone. Open Data Marketplace fosters a collaborative hub for data enthusiasts to explore, share, and contribute to a vast collection of datasets.
First ever open hub for data enthusiasts to collaborate and innovate. A platform to explore, share, and contribute to a vast collection of datasets. Through robust quality control and innovative technologies like blockchain verification, opendatabay ensures the authenticity and reliability of datasets, empowering users to make data-driven decisions with confidence. Leverage cutting-edge AI technologies to enhance the data exploration, analysis, and discovery experience.
From intelligent search and recommendations to automated data productisation and quotation, Opendatabay AI-driven features streamline the data workflow. Finding the data you need shouldn't be a complex. Opendatabay simplifies the data acquisition process with an intuitive interface and robust search tools. Effortlessly explore, discover, and access the data you need, allowing you to focus on extracting valuable insights. Opendatabay breaks new ground with a dedicated, AI-generated, synthetic datasets.
Leverage these privacy-preserving datasets for training and testing AI models without compromising sensitive information. Opendatabay prioritizes transparency by providing detailed metadata, provenance information, and usage guidelines for each dataset, ensuring users have a comprehensive understanding of the data they're working with. By leveraging a powerful combination of distributed ledger technology and rigorous third-party audits Opendatabay ensures the authenticity and reliability of every dataset. Security is at the core of Opendatabay. Marketplace implements stringent security measures, including encryption, access controls, and regular vulnerability assessments, to safeguard your data and protect your privacy.
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
As Europe's leading economic powerhouse and the fourth-largest hashtag#economy globally, Germany stands at the forefront of innovation and industrial might. Renowned for its precision engineering and high-tech sectors, Germany's economic structure is heavily supported by a robust service industry, accounting for approximately 68% of its GDP. This economic clout and strategic geopolitical stance position Germany as a focal point in the global cyber threat landscape.
In the face of escalating global tensions, particularly those emanating from geopolitical disputes with nations like hashtag#Russia and hashtag#China, hashtag#Germany has witnessed a significant uptick in targeted cyber operations. Our analysis indicates a marked increase in hashtag#cyberattack sophistication aimed at critical infrastructure and key industrial sectors. These attacks range from ransomware campaigns to hashtag#AdvancedPersistentThreats (hashtag#APTs), threatening national security and business integrity.
🔑 Key findings include:
🔍 Increased frequency and complexity of cyber threats.
🔍 Escalation of state-sponsored and criminally motivated cyber operations.
🔍 Active dark web exchanges of malicious tools and tactics.
Our comprehensive report delves into these challenges, using a blend of open-source and proprietary data collection techniques. By monitoring activity on critical networks and analyzing attack patterns, our team provides a detailed overview of the threats facing German entities.
This report aims to equip stakeholders across public and private sectors with the knowledge to enhance their defensive strategies, reduce exposure to cyber risks, and reinforce Germany's resilience against cyber threats.
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
2. Objectives of
presentation
• Understand what is expected to be
done before starting research
• You will understand definition of
ontology, epistemology and
methodology.
• Economics is considered as an
example. However the analysis may be
applied for other branches of social
science.
Outcome expected:
You will have a basic understanding of
research process.
Research Methods 2
3. I-Me-Myself
profkprabhakar@outlook.com
@profkprabhakar
• I am Dr.K.Prabhakar
• Scholar from Oxford University (HDCA)
• Student of three Nobel Prize laureates in Economics
• Always consider myself to be zero everyday and learn
from everyone every day.
• Purpose of Life: To influence as many learners as
possible and either learn or co-learn.
• To be recognized as a researcher in mixed methods.
• Qualifications
• Doctorate in Social Forecasting and interdisciplinary study
of economics, sociology, Management. (Aligarh Muslim
University)
• MBA ( Indira Gandhi National Open University)
• Teacher Training at IIM ( Calcutta)
• What I am is due to my teachers, however knowledge
nomad and autodidact.
Research Methods 3
4. ONTOLOGY
• As a first approximation, ontology is the
study of "what is”. Ontological statements
are answers to questions of whether
something fundamentally exists or not
(e.g. numbers, institutions, or causal
relations).
• the most classical ontological question is
the following: "Is there a God?"
• Ontological questions and assumptions are
often determined prior to empirical
research.
• They represent a set of beliefs about the
nature of the world and to a certain extent
influence the questions researchers ask, as
well as the ways in which they do science.
Research Methods 4
5. Conceptual
Clarity
• Numbers ( We will discuss in the
next class)
• Institutions or organizations
• Causal relationships.
Research Methods 5
8. Central Problem
or Problems
addressed by
economy – SCDU
• Scarcity: Natural resources like land, capital, labour, and
energy are scarce and therefore the economic problem
lies in the processes of their distribution.
• Change: Economic organizations are constantly evolving,
the dynamics of this process are the distinctive
aspect of economics.
• Dominance: Power and domination of one group over
another in material as well as social terms is the driving
force of economic phenomena.
• Uncertainty: The future is uncertain and our knowledge
about it is fallible. Therefore, the beliefs we hold about
the future in order to deal with uncertainty, and changes
in these beliefs, are the central determinant of the
economy.
• These problems give rise to Volatility, Uncertainty,
Complexity and Ambiguity.
Research Methods 8
9. Knowing this
what kind of
economics you
will generate?
• Please write in a paper and submit to
the coordinator.
Research Methods 9
12. Things
• The "things" analysed range from the
small (individuals) to the very large
(systems). That does not mean that a
systemic perspective denies the existence
of individuals, but that according to such a
perspective systems are more important
when it comes to the economy.
• Micro: Individuals and their motivations,
relations, and actions.
• Meso: Groups and organisations (or
institutions such as embedded social
norms) like firms, sectors, specific markets,
as well as subsystems like the financial
system.
• Macro: Systems and structures like the
environment or capitalism.
Research Methods 12
15. Atomist-
Middle-
Contexual
• Atomist: Things like individuals, groups or
institutions have an independent
existence. Their motivations and beliefs
come from within themselves and their
identity and essence does not change due
to environmental alterations.
• Middle: Actors exist as independent
entities. Yet there are mechanisms at
higher levels, like context, which influence
these actors. An abstract analysis
therefore has to respect both individual
essences and those contextual elements,
which can be identified as crucial.
• Contextual: Things are always relational
and interdependent, therefore there is no
way to conceive of them as independent of
their context, since without the
interactions with the structure and other
actors in which they exist they would be
fundamentally different
Research Methods 15
16. How do we
consider time?
• This question asks whether it is more
appropriate to conceive time in terms
of states (e.g. time 1, time 2, …) and
then compare and relate them or
whether time is a continuous process,
which is not reversible and where there
is constant change and no convergence
to a fixed point.
Research Methods 16
17. Static-Middle-Dynamic
Static-Middle-Dynamic
• Static: Time is a succession of
states, which can be identified.
• Middle: Both static and procedural
elements are present in time.
• Dynamic: It is of primary
importance to think in a procedural
way, things are constantly changing
and evolving in time.
Research Methods 17
18. Epistemology
• Epistemology is the study of knowledge
and justified belief.
• It is concerned with questions like:
• What are the necessary and sufficient
conditions of knowledge?
• What are its sources?
• What is its structure, and what are its
limits?
• It addresses what we can know and how
we can arrive at knowledge.
• The way in which researchers answer
these and other epistemological questions
determines which assumptions they make
regarding the nature of their knowledge
claims about the world and the confidence
they assign to these statements.
Research Methods 18
19. Realism -
Constructivist
• Realism: there is a real world independent
of human conceptions and we can observe
it. This definition of realism differs from
the realism-instrumentalism dichotomy
regarding assumptions that have been
debated in economics following Milton
Friedman's 1953 Essays in Positive
Economics.
• Middle: There is a real world, but also a
discursive world. It is the latter in
which scientific access to the real world
takes place. The relationship between the
two is interdependent and complex.
• Constructivist: What we can observe and
talk about in the (social) sciences are only
interpretations produced by ourselves.
These interpretations give meaning and
thereby create the world. Hence, the task
of science is to understand those realms
of meaning.
Research Methods 19
20. How you are
going to drive
your
research?
• This question is concerned with whether a perspective
wants to apply a generalized theoretical framework on many
or all aspects of the economy or whether a specific issue or
phenomena is considered to be very important and thus has
to be analysed in depth while using different frameworks
and theories.
• Perspective Driven: a way of thinking about economic
interactions (e.g. in terms of incentives, equilibria or
relations of production) is deemed to be a good way of
getting insights about different objects. It is assumed that
this particular way of thinking is capable of yielding valuable
insights about all kinds of economic and social phenomena.
• Contested: Both tendencies are present. A particular object
is of interest but a certain way of thinking is thought to be
useful as well. There is a degree of conflict between those
who try to move the perspective (or the discipline as a
whole) to one of the two categories.
• Object Driven: A particular object is deemed to be very
interesting and decisive for economic understanding. Hence,
the object is analysed from a wide array of different ways of
thinking.
Research Methods 20
21. Methodology
• Methodology refers to the question of
how to determine what counts as
justified knowledge.
• Often, methodological discussions
establish a set of rules or conditions
that have to be met in order for
something to be scientific.
• A certain methodological standpoint
often advocates specific research
methods over others, since they are
perceived to meet the requirements
for knowledge in a more satisfactory
and appropriate way than alternative
forms of inquiry.
Research Methods 21
23. Which
Methodology to
use or what is
your research
design?
• Qualitative
• Quantitative
• Mixed methods
Research Methods 23
24. Hypotheses
• Hypotheses are proposals for explaining or
understanding a certain phenomenon.
They can be derived from already existing
theory (logic, for example), from empirical
observations or from a combination of the
two.
• Deductive: New hypotheses are logically
derived from a set of axioms and
established laws.
• Middle: Axioms, empirical observations
and conceptualizations are intertwined
and the researcher goes back and forth
whilst developing the hypothesis
(associated concepts are abduction,
retroduction, dialectics).
• Inductive: Empirical observations and
generalizations based on observations lead
to new hypotheses.
Research Methods 24
25. Abductive
reasoning and
Retroduction
• Abductive reasoning is to abduce (or
take away) a logical assumption,
explanation, inference, conclusion,
hypothesis, or best guess from an
observation or set of observations.
Because the conclusion is merely a best
guess, the conclusion that is drawn
may or may not be true.
• Retroduction is the provisional
adoption of a hypothesis, because
every possible consequence of it is
capable of experimental verification, so
that the persevering application of the
same method may be expected to
reveal its disagreement with facts, if it
does so disagree.
Research Methods 25
26. How can we
generate and
evaluate a theory
or a hypothesis at
the abstract level
• Answers to this question illustrate the
importance different perspectives attach to
logical coherence, formalism and long chains of
reasoning when judging whether a hypothesis
is scientific or not. Perspectives that reject
these standards as criteria for science choose
to engage in a broad variety of practices and
reasoning, even though these might appear to
be contradictory in the light of classical logic.
• Formalistic: The hypothesis can be derived
from axioms in a logical way. There were no
logical mistakes made.
• Middle: Formalistic logic as well as other forms
of reasoning are applied.
• Broad reasoning: Non-formalistic techniques
such as counterfactuals, thought experiments,
deconstruction, (changing) conceptualizations
and fuzzy sets, heuristics, storytelling, etc. are
applied in order to assess the validity of a
hypothesis in a more crude and less exact
manner.
Research Methods 26
27. How can we relate a theory or a hypothesis to
reality?
• This question assesses how empirical observation is conceptualized by different
perspectives. Some perspectives have very clear cut rules on how to collect and
make sense of empirical observations and data. Others use ways that are less
specified and may vary depending on the nature of the research.
• Standardised and prescriptive methodology: Empirical testing is carried out in a
standard and prescribed way, which can be justified by reference to both the
philosophy of science and scientific practice. A prominent example
is the scientific method.
• Middle: A combination of standardized ways of relating theory to the world and
non-standard instruments.
• Idiosyncratic: An adequate way of referring to reality depends on more research
and is always context dependent. This category refers to methods which are only
defined in very broad terms such as process tracing.
Research Methods 27
28. Post Keynesian
Economics
• Effective demand
• Tendency to instability (e.g by animal
spirits)
• Capitalist monetary production
economy
• Macro economic paradoxes
• Fundamental uncertainty
• Hierarchy of markets
• Endogenous money creation
• Path dependency and historical time
• Non-neutrality of money
Research Methods 28
Editor's Notes
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Let us consider ONTOLOGY. It is the study of “What is”. It answers the questions of whether something fundamentally exists or not. You need to find what are existing. The institutions.
1.We will spend one hour on what are numbers or projections? In quantitative analysis we study projections.
2. Institutions.