This document provides an overview of experimental methods for social scientists. It discusses key concepts in causal inference and experimental design such as treatment, randomization, and measurement. Randomization techniques covered include simple random assignment, block randomization, and cluster randomization. Ethical considerations in experimentation are also reviewed. The document aims to help researchers design effective experiments and interpret their results causally.
By the end of this presentation you should be able to:
Describe the justification of qualitative Sampling Techniques
Understand different types of Sampling Techniques
The document provides guidance on conducting research. It recommends identifying an issue or problem to study, reviewing existing literature on the topic, planning and conducting a study, and publishing the results. It then discusses different dimensions of research projects, including the topic, novelty, scope, methodology, and intended utility. Finally, it notes that most research projects involve elements from multiple dimensions and can be positioned in a multidimensional conceptual space.
This document discusses the importance and applications of quantitative research across various fields including anthropology, communication, sports medicine, medical education, behavioral sciences, education/psychology, and social sciences. It provides examples of quantitative research questions and methods used in these fields, including experiments, surveys, and correlational studies. The key aspects of experimental design are outlined, including the need for treatment and control groups, random assignment, pre-and post-testing, and how field experiments differ from lab experiments.
Sampling Techniques literture-Dr. Yasser Mohammed Hassanain Elsayed.pptxYasserMohammedHassan1
The document provides definitions and explanations of key concepts related to sampling techniques used in research. It discusses the differences between a population and a sample, and describes several probability and non-probability sampling methods, including simple random sampling, systematic sampling, stratified sampling, cluster sampling, and non-probability sampling. The document emphasizes the importance of selecting the appropriate sampling technique based on the research question and of clearly explaining the sampling method used in research studies.
Research Methods 2 for Midwifery students .pptxEndex Tam
The document discusses measures of association in case-control studies and cohort studies. It defines odds ratio as the measure of association in case-control studies, which compares the odds of disease in the exposed group to the odds of disease in the unexposed group. Cohort studies follow disease-free groups over time to compare incidence of disease between exposed and unexposed cohorts. The relative risk is used to measure association in cohort studies by comparing incidence rates of disease between exposed and unexposed groups. The document also discusses experimental study designs, sampling methods, and how to determine sample size.
Doing sociological research involves applying the sociological perspective, being curious and asking questions objectively. There are different types of truths and ways of knowing, including scientific knowledge based on empirical evidence. Sociological research methods include positivist, interpretive, and critical sociology. Key aspects of research are concepts, variables, measurement, validity, reliability, and the relationship between variables. The scientific method involves collecting data through observation and experimentation. Common data collection methods are participant observation, interviews, surveys, existing sources, and experiments. It is important for sociological research to be objective and consider how factors like gender can influence results. Ethical standards help ensure research protects participants.
This document provides an overview of key concepts in psychology and research methods, including:
- Different approaches to psychology like psychodynamic, behavioral, cognitive.
- Common research methods like observation, surveys, experiments, and longitudinal studies.
- Key terms like independent and dependent variables, experimental and control groups.
- Ethical standards for psychological research involving informed consent and protecting participants.
- Ways of organizing data like frequency distributions, and measures of central tendency and variability like mean, median, and standard deviation.
By the end of this presentation you should be able to:
Describe the justification of qualitative Sampling Techniques
Understand different types of Sampling Techniques
The document provides guidance on conducting research. It recommends identifying an issue or problem to study, reviewing existing literature on the topic, planning and conducting a study, and publishing the results. It then discusses different dimensions of research projects, including the topic, novelty, scope, methodology, and intended utility. Finally, it notes that most research projects involve elements from multiple dimensions and can be positioned in a multidimensional conceptual space.
This document discusses the importance and applications of quantitative research across various fields including anthropology, communication, sports medicine, medical education, behavioral sciences, education/psychology, and social sciences. It provides examples of quantitative research questions and methods used in these fields, including experiments, surveys, and correlational studies. The key aspects of experimental design are outlined, including the need for treatment and control groups, random assignment, pre-and post-testing, and how field experiments differ from lab experiments.
Sampling Techniques literture-Dr. Yasser Mohammed Hassanain Elsayed.pptxYasserMohammedHassan1
The document provides definitions and explanations of key concepts related to sampling techniques used in research. It discusses the differences between a population and a sample, and describes several probability and non-probability sampling methods, including simple random sampling, systematic sampling, stratified sampling, cluster sampling, and non-probability sampling. The document emphasizes the importance of selecting the appropriate sampling technique based on the research question and of clearly explaining the sampling method used in research studies.
Research Methods 2 for Midwifery students .pptxEndex Tam
The document discusses measures of association in case-control studies and cohort studies. It defines odds ratio as the measure of association in case-control studies, which compares the odds of disease in the exposed group to the odds of disease in the unexposed group. Cohort studies follow disease-free groups over time to compare incidence of disease between exposed and unexposed cohorts. The relative risk is used to measure association in cohort studies by comparing incidence rates of disease between exposed and unexposed groups. The document also discusses experimental study designs, sampling methods, and how to determine sample size.
Doing sociological research involves applying the sociological perspective, being curious and asking questions objectively. There are different types of truths and ways of knowing, including scientific knowledge based on empirical evidence. Sociological research methods include positivist, interpretive, and critical sociology. Key aspects of research are concepts, variables, measurement, validity, reliability, and the relationship between variables. The scientific method involves collecting data through observation and experimentation. Common data collection methods are participant observation, interviews, surveys, existing sources, and experiments. It is important for sociological research to be objective and consider how factors like gender can influence results. Ethical standards help ensure research protects participants.
This document provides an overview of key concepts in psychology and research methods, including:
- Different approaches to psychology like psychodynamic, behavioral, cognitive.
- Common research methods like observation, surveys, experiments, and longitudinal studies.
- Key terms like independent and dependent variables, experimental and control groups.
- Ethical standards for psychological research involving informed consent and protecting participants.
- Ways of organizing data like frequency distributions, and measures of central tendency and variability like mean, median, and standard deviation.
This document provides an introduction to quantitative and qualitative research methods. It discusses key aspects of research design including ontology, epistemology, methodology, and methods. Quantitative research uses numerical data and statistical analysis, while qualitative research uses non-numerical data sources like interviews. The appropriate approach depends on one's research questions, philosophy, and skills. Both approaches have strengths and limitations.
This document provides an introduction to quantitative and qualitative research methods. It discusses key aspects of research design including ontology, epistemology, methodology, and methods. Quantitative research uses numerical data and statistical analysis, while qualitative research uses non-numerical data sources like interviews. The appropriate approach depends on the research questions and philosophy. Both have benefits and limitations. Validity, reliability, and trustworthiness are also important aspects of research quality.
This document provides an introduction to quantitative and qualitative research methods. It discusses that research methods can be broadly split into quantitative and qualitative approaches. The choice of method depends on the research questions, underlying philosophy, and researcher's skills and preferences. It also outlines some basic principles of research design including ontology, epistemology, methodology, and specific methods. Common quantitative and qualitative data collection and analysis techniques are also introduced.
Introduction to quantitative and qualitative researchLiz FitzGerald
This presentation, delivered in an Open University CALRG Building Knowledge session, gives a preliminary introduction to both quantitative and qualitative research approaches. There has been widespread debate when considering the relative merits of quantitative and qualitative strategies for research. Positions taken by individual researchers vary considerably, from those who see the two strategies as entirely separate, polar opposites that are based upon alternative views of the world, to those who are happy to mix these strategies within their research projects. We consider the different strengths, weaknesses and suitability of different approaches and draw upon some examples to highlight their use within educational technology.
UPDATED-Quantitative-Methods for PrelimsMarvin158667
This document provides an overview of quantitative research methods and modeling/simulations. It defines quantitative research as using numbers and statistics to test theories about an identified problem. The document outlines different types of quantitative methods like experiments, quasi-experiments, and surveys. It also compares quantitative and qualitative approaches and defines key concepts for quantitative research like variables, populations, sampling, and different sampling methods.
This is the presentation I made to the National Cancer Institute's Cancer Research in the Media workshop for Latin American journalists in Guadalajara on November 8, 2011. It is step-by-step advice about things to consider about each of the 10 criteria we apply to the review of health care news stories about treatments, tests, products & procedures.
The document discusses various sampling strategies used in qualitative research. It defines key concepts like population, sample, sampling frame, and parameters. It describes probability sampling techniques that give all units an equal chance of selection as well as non-probability techniques like convenience sampling, quota sampling, purposive sampling, snowball sampling, deviant case sampling, and adaptive sampling. Each technique is explained along with examples of how and when it would be used to gather samples in qualitative research.
This document discusses data collection and measurement. It defines different levels of measurement including nominal, ordinal, interval and ratio. It explains the data collection process and questions to consider like what, how, who, where and when to collect data. Common data collection methods are identified like surveys, interviews and physiological measures. Factors to consider when selecting a data collection instrument are discussed like practicality, reliability and validity. The document provides examples to illustrate key concepts.
This lecture talks about the importance of evidence in scientific, business, and innovation research. It lists down important examples to carry this process in perspective of the problem statement.
This document discusses case studies and clinical studies as research methods. It provides information on what case studies and clinical studies are, how they are conducted in different fields like business and psychology, and the typical components of a case study or clinical study such as facts from interviews, tests administered, and recommendations. The key aspects covered are that case studies involve an in-depth analysis of a limited number of situations while clinical studies involve research with human participants to further medical knowledge.
The Social Transmission of Choice: An Exploratory Computer Simulation with Ap...Edmund Chattoe-Brown
Paper presented at the British Sociological Association Annual Conference (Social Connections: Identities, Technologies, Relationships), University of East London, 12-14 April.
This document discusses various sampling methods used in research. It begins by introducing the objectives of understanding different sampling techniques and distinguishing between probability and non-probability sampling. It then presents several interactive activities to recall key terms related to research methodology. The document proceeds to define sampling and describe different probability sampling methods like simple random sampling, systematic sampling, stratified sampling, and cluster sampling. It also outlines various non-probability sampling techniques including quota sampling, voluntary sampling, purposive sampling, availability sampling, and snowball sampling. The document concludes by discussing how to avoid sampling errors and providing an assignment for groups to develop research instruments.
The document discusses various sampling methods used in statistics. It defines key terms like population, sample, sampling, and explains the purposes of sampling. It describes different probability sampling methods like simple random sampling, systematic sampling, cluster sampling and stratified sampling. It also discusses potential sources of bias and error in sampling like sampling error, sampling bias, and non-sampling error. The document provides examples to illustrate different sampling techniques and their advantages and disadvantages.
This document provides an overview of qualitative research methods. It discusses various qualitative research designs including case studies, comparative studies, retrospective studies, and longitudinal qualitative studies. It also covers qualitative research sampling techniques like theoretical sampling and purposive sampling. Common qualitative study designs such as ethnography, phenomenology, grounded theory, and participatory action research are defined. The document also discusses principles of qualitative research including saturation, appropriateness of the approach, and fitting the approach into the research process.
The document discusses research in nursing. It defines research and describes the roles of nurses in research from producer to consumer. The importance of research to the nursing profession is outlined as building nursing knowledge, validating improvements, and making healthcare more efficient. The sources and types of knowledge and reasoning in research are examined, including basic and applied research. The history of nursing research from Florence Nightingale to modern evidence-based practice is summarized.
This document discusses various study designs and methodologies used in quantitative research. It begins by outlining the objectives and possible subsections of a methodology section. It then discusses study area, period, and population. The document explains how to choose study designs and describes descriptive, case-control, cohort, experimental, and mixed methods designs. It provides details on variables, sampling techniques, data collection tools, and analyses. Overall, the document serves as a guide for planning and conducting quantitative research studies.
Meyer primr-sililcon flatirons expanded facebook slide deckMichelle N. Meyer
Facebook conducted experiments on over 600,000 unwitting users to study how emotional content on the platform can spread and influence users' moods and posting behaviors. The experiments involved algorithmically reducing the amount of positive or negative posts users were shown in their news feeds for one week periods. Results found small effects, with exposure to fewer positive posts linked to slightly more negative language use and vice versa. Critics argue the research violated ethics guidelines by manipulating users without consent. Supporters counter that the risks were minimal and provided valuable insights to help Facebook understand and mitigate potential real harms from regular platform use.
Maslow's hierarchy of needs is a five-tier model that categorizes basic human needs into deficiency and growth needs. Deficiency needs include physiological needs, safety, love and belonging, and esteem. Growth needs refer to self-actualization. There are three theories of audiences: passive audiences who consume media, active audiences who make choices, and interactive audiences influenced by new media. The hypodermic needle model views audiences as passive and vulnerable to direct media messaging. Cultivation theory suggests television shapes viewers' worldviews over time, with heavy viewers more susceptible to influence. The two-step flow theory and uses and gratifications model view audiences as more active in selecting media to fulfill needs.
How To Read A Medical Paper: Part 2, Assessing the Methodological QualityDrLukeKane
This document outlines five essential questions to ask when assessing the methodological quality of papers: 1) Was the study original? 2) Whom is the study about? 3) Was the design of the study sensible? 4) Was systematic bias avoided or minimized? 5) Was the study large enough and long enough to make the results credible? It discusses factors to consider for each question when evaluating a study's methods section such as sample size, duration of follow up, and completeness of follow up.
This document discusses 13 sources of research problems: 1) personal experience, 2) practical experience, 3) critical appraisal of literature, 4) previous research, 5) existing theories, 6) consumer feedback, 7) performance improvement activities, 8) social issues, 9) brainstorming, 10) intuition, 11) folklores, 12) exposure to field situations, and 13) consultations with experts. It provides examples for several of the sources to illustrate how experiences, literature reviews, theories, feedback, and more can inspire questions for further investigation and help identify significant problems to study.
This document provides an introduction to quantitative and qualitative research methods. It discusses key aspects of research design including ontology, epistemology, methodology, and methods. Quantitative research uses numerical data and statistical analysis, while qualitative research uses non-numerical data sources like interviews. The appropriate approach depends on one's research questions, philosophy, and skills. Both approaches have strengths and limitations.
This document provides an introduction to quantitative and qualitative research methods. It discusses key aspects of research design including ontology, epistemology, methodology, and methods. Quantitative research uses numerical data and statistical analysis, while qualitative research uses non-numerical data sources like interviews. The appropriate approach depends on the research questions and philosophy. Both have benefits and limitations. Validity, reliability, and trustworthiness are also important aspects of research quality.
This document provides an introduction to quantitative and qualitative research methods. It discusses that research methods can be broadly split into quantitative and qualitative approaches. The choice of method depends on the research questions, underlying philosophy, and researcher's skills and preferences. It also outlines some basic principles of research design including ontology, epistemology, methodology, and specific methods. Common quantitative and qualitative data collection and analysis techniques are also introduced.
Introduction to quantitative and qualitative researchLiz FitzGerald
This presentation, delivered in an Open University CALRG Building Knowledge session, gives a preliminary introduction to both quantitative and qualitative research approaches. There has been widespread debate when considering the relative merits of quantitative and qualitative strategies for research. Positions taken by individual researchers vary considerably, from those who see the two strategies as entirely separate, polar opposites that are based upon alternative views of the world, to those who are happy to mix these strategies within their research projects. We consider the different strengths, weaknesses and suitability of different approaches and draw upon some examples to highlight their use within educational technology.
UPDATED-Quantitative-Methods for PrelimsMarvin158667
This document provides an overview of quantitative research methods and modeling/simulations. It defines quantitative research as using numbers and statistics to test theories about an identified problem. The document outlines different types of quantitative methods like experiments, quasi-experiments, and surveys. It also compares quantitative and qualitative approaches and defines key concepts for quantitative research like variables, populations, sampling, and different sampling methods.
This is the presentation I made to the National Cancer Institute's Cancer Research in the Media workshop for Latin American journalists in Guadalajara on November 8, 2011. It is step-by-step advice about things to consider about each of the 10 criteria we apply to the review of health care news stories about treatments, tests, products & procedures.
The document discusses various sampling strategies used in qualitative research. It defines key concepts like population, sample, sampling frame, and parameters. It describes probability sampling techniques that give all units an equal chance of selection as well as non-probability techniques like convenience sampling, quota sampling, purposive sampling, snowball sampling, deviant case sampling, and adaptive sampling. Each technique is explained along with examples of how and when it would be used to gather samples in qualitative research.
This document discusses data collection and measurement. It defines different levels of measurement including nominal, ordinal, interval and ratio. It explains the data collection process and questions to consider like what, how, who, where and when to collect data. Common data collection methods are identified like surveys, interviews and physiological measures. Factors to consider when selecting a data collection instrument are discussed like practicality, reliability and validity. The document provides examples to illustrate key concepts.
This lecture talks about the importance of evidence in scientific, business, and innovation research. It lists down important examples to carry this process in perspective of the problem statement.
This document discusses case studies and clinical studies as research methods. It provides information on what case studies and clinical studies are, how they are conducted in different fields like business and psychology, and the typical components of a case study or clinical study such as facts from interviews, tests administered, and recommendations. The key aspects covered are that case studies involve an in-depth analysis of a limited number of situations while clinical studies involve research with human participants to further medical knowledge.
The Social Transmission of Choice: An Exploratory Computer Simulation with Ap...Edmund Chattoe-Brown
Paper presented at the British Sociological Association Annual Conference (Social Connections: Identities, Technologies, Relationships), University of East London, 12-14 April.
This document discusses various sampling methods used in research. It begins by introducing the objectives of understanding different sampling techniques and distinguishing between probability and non-probability sampling. It then presents several interactive activities to recall key terms related to research methodology. The document proceeds to define sampling and describe different probability sampling methods like simple random sampling, systematic sampling, stratified sampling, and cluster sampling. It also outlines various non-probability sampling techniques including quota sampling, voluntary sampling, purposive sampling, availability sampling, and snowball sampling. The document concludes by discussing how to avoid sampling errors and providing an assignment for groups to develop research instruments.
The document discusses various sampling methods used in statistics. It defines key terms like population, sample, sampling, and explains the purposes of sampling. It describes different probability sampling methods like simple random sampling, systematic sampling, cluster sampling and stratified sampling. It also discusses potential sources of bias and error in sampling like sampling error, sampling bias, and non-sampling error. The document provides examples to illustrate different sampling techniques and their advantages and disadvantages.
This document provides an overview of qualitative research methods. It discusses various qualitative research designs including case studies, comparative studies, retrospective studies, and longitudinal qualitative studies. It also covers qualitative research sampling techniques like theoretical sampling and purposive sampling. Common qualitative study designs such as ethnography, phenomenology, grounded theory, and participatory action research are defined. The document also discusses principles of qualitative research including saturation, appropriateness of the approach, and fitting the approach into the research process.
The document discusses research in nursing. It defines research and describes the roles of nurses in research from producer to consumer. The importance of research to the nursing profession is outlined as building nursing knowledge, validating improvements, and making healthcare more efficient. The sources and types of knowledge and reasoning in research are examined, including basic and applied research. The history of nursing research from Florence Nightingale to modern evidence-based practice is summarized.
This document discusses various study designs and methodologies used in quantitative research. It begins by outlining the objectives and possible subsections of a methodology section. It then discusses study area, period, and population. The document explains how to choose study designs and describes descriptive, case-control, cohort, experimental, and mixed methods designs. It provides details on variables, sampling techniques, data collection tools, and analyses. Overall, the document serves as a guide for planning and conducting quantitative research studies.
Meyer primr-sililcon flatirons expanded facebook slide deckMichelle N. Meyer
Facebook conducted experiments on over 600,000 unwitting users to study how emotional content on the platform can spread and influence users' moods and posting behaviors. The experiments involved algorithmically reducing the amount of positive or negative posts users were shown in their news feeds for one week periods. Results found small effects, with exposure to fewer positive posts linked to slightly more negative language use and vice versa. Critics argue the research violated ethics guidelines by manipulating users without consent. Supporters counter that the risks were minimal and provided valuable insights to help Facebook understand and mitigate potential real harms from regular platform use.
Maslow's hierarchy of needs is a five-tier model that categorizes basic human needs into deficiency and growth needs. Deficiency needs include physiological needs, safety, love and belonging, and esteem. Growth needs refer to self-actualization. There are three theories of audiences: passive audiences who consume media, active audiences who make choices, and interactive audiences influenced by new media. The hypodermic needle model views audiences as passive and vulnerable to direct media messaging. Cultivation theory suggests television shapes viewers' worldviews over time, with heavy viewers more susceptible to influence. The two-step flow theory and uses and gratifications model view audiences as more active in selecting media to fulfill needs.
How To Read A Medical Paper: Part 2, Assessing the Methodological QualityDrLukeKane
This document outlines five essential questions to ask when assessing the methodological quality of papers: 1) Was the study original? 2) Whom is the study about? 3) Was the design of the study sensible? 4) Was systematic bias avoided or minimized? 5) Was the study large enough and long enough to make the results credible? It discusses factors to consider for each question when evaluating a study's methods section such as sample size, duration of follow up, and completeness of follow up.
This document discusses 13 sources of research problems: 1) personal experience, 2) practical experience, 3) critical appraisal of literature, 4) previous research, 5) existing theories, 6) consumer feedback, 7) performance improvement activities, 8) social issues, 9) brainstorming, 10) intuition, 11) folklores, 12) exposure to field situations, and 13) consultations with experts. It provides examples for several of the sources to illustrate how experiences, literature reviews, theories, feedback, and more can inspire questions for further investigation and help identify significant problems to study.
Similar to POP77034 Experimental Methods HT2023 week 2 slides.pdf (20)
Strategies for Effective Upskilling is a presentation by Chinwendu Peace in a Your Skill Boost Masterclass organisation by the Excellence Foundation for South Sudan on 08th and 09th June 2024 from 1 PM to 3 PM on each day.
it describes the bony anatomy including the femoral head , acetabulum, labrum . also discusses the capsule , ligaments . muscle that act on the hip joint and the range of motion are outlined. factors affecting hip joint stability and weight transmission through the joint are summarized.
How to Setup Warehouse & Location in Odoo 17 InventoryCeline George
In this slide, we'll explore how to set up warehouses and locations in Odoo 17 Inventory. This will help us manage our stock effectively, track inventory levels, and streamline warehouse operations.
Chapter wise All Notes of First year Basic Civil Engineering.pptxDenish Jangid
Chapter wise All Notes of First year Basic Civil Engineering
Syllabus
Chapter-1
Introduction to objective, scope and outcome the subject
Chapter 2
Introduction: Scope and Specialization of Civil Engineering, Role of civil Engineer in Society, Impact of infrastructural development on economy of country.
Chapter 3
Surveying: Object Principles & Types of Surveying; Site Plans, Plans & Maps; Scales & Unit of different Measurements.
Linear Measurements: Instruments used. Linear Measurement by Tape, Ranging out Survey Lines and overcoming Obstructions; Measurements on sloping ground; Tape corrections, conventional symbols. Angular Measurements: Instruments used; Introduction to Compass Surveying, Bearings and Longitude & Latitude of a Line, Introduction to total station.
Levelling: Instrument used Object of levelling, Methods of levelling in brief, and Contour maps.
Chapter 4
Buildings: Selection of site for Buildings, Layout of Building Plan, Types of buildings, Plinth area, carpet area, floor space index, Introduction to building byelaws, concept of sun light & ventilation. Components of Buildings & their functions, Basic concept of R.C.C., Introduction to types of foundation
Chapter 5
Transportation: Introduction to Transportation Engineering; Traffic and Road Safety: Types and Characteristics of Various Modes of Transportation; Various Road Traffic Signs, Causes of Accidents and Road Safety Measures.
Chapter 6
Environmental Engineering: Environmental Pollution, Environmental Acts and Regulations, Functional Concepts of Ecology, Basics of Species, Biodiversity, Ecosystem, Hydrological Cycle; Chemical Cycles: Carbon, Nitrogen & Phosphorus; Energy Flow in Ecosystems.
Water Pollution: Water Quality standards, Introduction to Treatment & Disposal of Waste Water. Reuse and Saving of Water, Rain Water Harvesting. Solid Waste Management: Classification of Solid Waste, Collection, Transportation and Disposal of Solid. Recycling of Solid Waste: Energy Recovery, Sanitary Landfill, On-Site Sanitation. Air & Noise Pollution: Primary and Secondary air pollutants, Harmful effects of Air Pollution, Control of Air Pollution. . Noise Pollution Harmful Effects of noise pollution, control of noise pollution, Global warming & Climate Change, Ozone depletion, Greenhouse effect
Text Books:
1. Palancharmy, Basic Civil Engineering, McGraw Hill publishers.
2. Satheesh Gopi, Basic Civil Engineering, Pearson Publishers.
3. Ketki Rangwala Dalal, Essentials of Civil Engineering, Charotar Publishing House.
4. BCP, Surveying volume 1
Temple of Asclepius in Thrace. Excavation resultsKrassimira Luka
The temple and the sanctuary around were dedicated to Asklepios Zmidrenus. This name has been known since 1875 when an inscription dedicated to him was discovered in Rome. The inscription is dated in 227 AD and was left by soldiers originating from the city of Philippopolis (modern Plovdiv).
LAND USE LAND COVER AND NDVI OF MIRZAPUR DISTRICT, UPRAHUL
This Dissertation explores the particular circumstances of Mirzapur, a region located in the
core of India. Mirzapur, with its varied terrains and abundant biodiversity, offers an optimal
environment for investigating the changes in vegetation cover dynamics. Our study utilizes
advanced technologies such as GIS (Geographic Information Systems) and Remote sensing to
analyze the transformations that have taken place over the course of a decade.
The complex relationship between human activities and the environment has been the focus
of extensive research and worry. As the global community grapples with swift urbanization,
population expansion, and economic progress, the effects on natural ecosystems are becoming
more evident. A crucial element of this impact is the alteration of vegetation cover, which plays a
significant role in maintaining the ecological equilibrium of our planet.Land serves as the foundation for all human activities and provides the necessary materials for
these activities. As the most crucial natural resource, its utilization by humans results in different
'Land uses,' which are determined by both human activities and the physical characteristics of the
land.
The utilization of land is impacted by human needs and environmental factors. In countries
like India, rapid population growth and the emphasis on extensive resource exploitation can lead
to significant land degradation, adversely affecting the region's land cover.
Therefore, human intervention has significantly influenced land use patterns over many
centuries, evolving its structure over time and space. In the present era, these changes have
accelerated due to factors such as agriculture and urbanization. Information regarding land use and
cover is essential for various planning and management tasks related to the Earth's surface,
providing crucial environmental data for scientific, resource management, policy purposes, and
diverse human activities.
Accurate understanding of land use and cover is imperative for the development planning
of any area. Consequently, a wide range of professionals, including earth system scientists, land
and water managers, and urban planners, are interested in obtaining data on land use and cover
changes, conversion trends, and other related patterns. The spatial dimensions of land use and
cover support policymakers and scientists in making well-informed decisions, as alterations in
these patterns indicate shifts in economic and social conditions. Monitoring such changes with the
help of Advanced technologies like Remote Sensing and Geographic Information Systems is
crucial for coordinated efforts across different administrative levels. Advanced technologies like
Remote Sensing and Geographic Information Systems
9
Changes in vegetation cover refer to variations in the distribution, composition, and overall
structure of plant communities across different temporal and spatial scales. These changes can
occur natural.
2. The plan for today
• Quick causal inference recap
• Experimental design
• Ethics
• Next week: more experimental design
2
3. The Fundamental Problem of Causal Inference
• It is impossible to observe any unit we’re interested in (e.g., person, country,
fi
rm, school) both when it has and has not been changed by a causal action
• Only in physics and chemistry are units (particles, molecules)
interchangeable (“exchangeable”) enough that we don’t have to worry
about this
• If I give 100 euros to Mary and she gets happier than she was before, we
fundamentally cannot know how happy she would have been if I had not
given her 100 euros
• We can use theory, intuition, anecdote, data to come up with a (very) good
guess
• But we can never be sure
6. That’s experiments in theory, what about in practice?
Real-world implementation of experiments is di
ffi
cult!
• When you assign a unit (e.g. person) to treatment, they may not actually take
that treatment
• You give them a drug but they don’t take it
• You send them a YouTube video to watch but they don’t watch it, or they
mute it and don’t pay attention
• Same for the control group
• They may go out and
fi
nd the drug themselves, or stumble on the YouTube
video
7. That’s experiments in theory, what about in practice?
• “Compliers are subjects who will take the treatment if and only if they were
assigned to the treatment group…
• Non-compliers are composed of the three remaining subgroups:
• Always-takers are subjects who will always take the treatment even if they
were assigned to the control group
• Never-takers are subjects who will never take the treatment even if they
were assigned to the treatment group
• De
fi
ers are subjects who will do the opposite of their treatment assignment
status” https://en.wikipedia.org/wiki/Local_average_treatment_e
ff
ect
8. Experimental design
• Experiments have three “main” components:
• Treatment
• Randomization into treatment and control groups
• Measurement of outcome
• Let’s look at each of these components in turn
• Also look at groupings of these that form common ‘types’
of experiments
8
9. Designing a treatment
Good treatments
• “One hopes that the treatment alters values of the independent variable (e.g., causes
subjects to think about campaign
fi
nance in terms of free speech) or induces certain
beliefs among participants (e.g., how much they will get paid).” (Druckman 2020 p.82)
• The treatment should:
• Be e
ffi
cacious
• Fit with the theoretical construct the researcher is interested in
• Vitamin D and…beach holiday? Multivitamin? Stern lecture from doctor?
• Support for Putin and…seeing an o
ffi
cial arrested for corruption? Watching a Navalny
video about regime corruption? Reading a TI report about Russian corruption levels?
• Have a basis in theory
• How will the knowledge gained from the experiment
fi
t in with other things we know
about the world?
9
10. Designing a treatment
Validation, piloting
• “When it comes to evaluating treatments, researchers should not
trust themselves to validate them.
• A crucial step taken in the design of an experiment entails validating
the intervention with a sample that matches the experimental
participants and/or the participants themselves.”
• “One need not test the outcome variables of interest but instead
assess whether participants interpret and react to the intervention
as presumed (e.g., increased anxiety or social trust)
10
11. Designing a treatment
Validation, piloting 2
• Piloting has the advantage of allowing one to evaluate di
ff
erent
approaches before implementing the actual experiment
• Ideally, one pilots on a sample drawn from the same population as
the experiment
• If that is not possible, however, one should carefully think about
possible di
ff
erences between the pilot sample and the
experimental sample”
11
12. Designing a treatment
Manipulation checks
• “In addition to piloting, one can incorporate a manipulation check
into the experiment itself to empirically assess whether respondents
receive and perceive the treatment as intended.”
• Example: experiment on whether seeing a news report from Fox
News leads people to vote for Republicans more than a CNN report
• Manipulation check: ask what the source of the clip was
• Downsides: extra cost, be careful with outcome measurement
12
13. Measurement and validity
Druckman 2020 p.87, 93
• Experiments are usually*
taken to have good
internal validity and
‘statistical conclusion
validity’
• Good treatment design,
measurement,
randomization will help
ensure the
fi
rst three of
these types of validity
13
14. External validity and generalizability
Druckman p.94-102
• “External validity means generalizing across 1) samples, 2) settings, 3)
treatments, and 4) outcome measures”
• What is being generalized?
• Existence of an e
ff
ect? Precise e
ff
ect size?
• To what are you generalizing?
• What population?
• The answers to these questions depend on the goals of the experiment
14
15. External validity and realism/naturalism
• Does it matter how realistic your treatment is?
• What is feasible and ethical?
• Example:
• Outcome: voting in an election
• Conceptual treatment: watching advertisements for a candidate
• Practical/actual treatment:
• Have participants watch 30 minutes of the news with advertisements
interspersed?
• Show a series of only advertisements? How many? How many times?
15
16. Other kinds of treatments
Encouragement design
• Intent-to-treat estimator
• “randomly incentivize subjects recruited via survey to follow one of two Twitter
accounts programmed to retweet posts by politically in
fl
uential users. Subjects were
periodically quizzed about the contents of their Twitter feeds and surveyed again to
gauge the e
ff
ect of exposure to counter-attitudinal social media content.” (Guess 2021)
• Shows the trade-o
ff
between naturalism and strength of treatment
• “Like the o
ffl
ine world, online environments are crowded and multifaceted, with
many competing demands on users’ attention.”
• People just don’t see or pay attention to stu
ff
!
• “at least in an intent-to-treat world, manipulating a single post, ad impression, or
account exposure may not in itself be expected to produce measurably large
e
ff
ects.”
16
18. Ethics
Morton & Williams Chapters 11-13
• Experiments must be
ethical!
• Harm or risk to participants
• Changing of important real-
world outcomes (e.g.,
elections)
• Deception
18
19. Ethics
Morton & Williams
• Bene
fi
ts vs. risks
• Harms
• Psychological harm
• Invasion of privacy or
con
fi
dentiality
19
20. Ethics
Morton & Williams
• Probability and magnitude of harm
• Compare to daily life and routine risks
• Vulnerable subjects
• Prisoners, children, disabled
• When possible, experiments need to get informed consent
• Not always feasible! This may be a foreign concept or may interfere with the
experiment
• “Informed consent has become a mainstay of research with human subjects because it
serves two purposes: (1) it ensures that the subjects are voluntarily participating and
that their autonomy is protected and (2) it provides researchers with legal protections in
case of unexpected events.”
20
21. Ethics
Morton & Williams Chapter 13
• Deception
• Concerns about contaminating a subject pool
• If you must use deception, you should probably debrief
21
22. Population and sample
• The population you wish to generalize to may be:
• All adult residents of Ireland
• All adult voters of Ireland
• Residents of Dublin between 18 and 45 years of age
• Or perhaps the population is irrelevant
• Your experiment will need to de
fi
ne a sample of that population on
which your treatment will be applied
22
23. Sampling
Druckman p.109-120
• How homogenous do you think the treatment is?
• If you’re interested in attitudes towards pension reform, your
sample may need su
ffi
cient young and old people
• Pharmaceuticals and biological sex
• Urban vs. rural residents
• Cost, generalizability, practicality
23
24. Sampling: Random samples
• Dial random telephone numbers
• Pick names out of a list (phonebook) randomly
• Where do you get the list??
• Not always legal or feasible
24
Druckman p.109-120
25. Sampling: Convenience samples
• Take whoever is convenient
• or whoever selects into your sample
• Put up posters, send out emails, buy advertisements
• Talk to people on the street
• Cheaper and easier, but sharply limits generalizability
25
Druckman p.109-120
26. Sampling: Weighting
• “Weighting requires that one obtain descriptive data of the target
population, typically demographics.
• For example, when the population includes all Americans, one can
use the U.S. Census…for demographic population
fi
gures.
• One then computes weights that account for each respondent’s
probability of being included in the sample
• For example, if the population consists of 50% men but the
sample contains only 40% men, then male sample respondents
will be weighted to count more in computations from the sample
(and women will be counted less)
26
Druckman p.109-120
27. Sampling: Weighting
• Survey researchers commonly use weights, even with many
probability samples, to ensure the accuracy of observational
inferences (e.g., the percentage of men who hold a particular
attitude)” (Druckman 2020 p.117)
• Consider weighting if:
• e
ff
ects are heterogeneous in a way you can correct for
• you care about the population
• you are interested in precise e
ff
ect size
27
Druckman p.109-120
28. Sample size and power
https://egap.org/resource/10-things-to-know-about-statistical-power/
• “Power is the ability to distinguish signal from noise.”
• “If our experiments are highly-powered, we can be con
fi
dent that if there truly is a
treatment e
ff
ect, we’ll be able to see it.”
• We want to avoid false negatives and false positives
• Example:
• “Now suppose an experiment instead used subjects’ income as an outcome variable.
• Incomes can vary pretty widely – in some places, it is not uncommon for people to
have neighbors that earn two, ten, or one hundred times their daily wages.
• When noise is high, experiments have more trouble.
• A treatment that increased workers’ incomes by 1% would be di
ffi
cult to detect,
because incomes di
ff
er by so much in the
fi
rst place.”
28
29. Sample size and power
https://egap.org/resource/10-things-to-know-about-statistical-power/
• The three ingredients of statistical power:
• Strength of the treatment
• Background noise
• As the background noise of your outcome variables increases, the power of
your experiment decreases
• To the extent that it is possible, try to select outcome variables that have low
variability
• In practical terms, this means comparing the standard deviation of the
outcome variable to the expected treatment e
ff
ect size
• Sample size
• See link for formula and calculator, but also beware! Power is a slippery thing
29
30. Sample size and power
https://egap.org/resource/10-things-to-know-about-statistical-power/
• https://www.stat.ubc.ca/~rollin/stats/ssize/n2.html
• https://machinelearningmastery.com/statistical-power-and-power-
analysis-in-python/
• “Statistical power is the probability of a hypothesis test of
fi
nding
an e
ff
ect if there is an e
ff
ect to be found.
• A power analysis can be used to estimate the minimum sample
size required for an experiment, given a desired signi
fi
cance level,
e
ff
ect size, and statistical power.”
30
31. Randomization
Random assignment to treatment and control groups
• So you’ve got your experimental design, a sample of people to
experiment on
• Now you need to assign people to treatment and control
• Otherwise it wouldn’t be an experiment!
• Simple randomization
• Complete simple randomization
• Block and cluster randomization
31
32. Randomization: Simple random assignment
Druckman 2020, p.109-120
• “Simple random assignment is a term of art, referring to a procedure—a die roll
or coin toss—that gives each subject an identical probability of being assigned
to the treatment group
• The practical drawback of simple random assignment is that when N is small,
random chance can create a treatment group that is larger or smaller than
what the researcher intended.” (FEDAI p.36)
• “A useful special case of simple random assignment is complete random
assignment, where exactly m of N units are assigned to the treatment group with
equal probability.”
• Be careful about de
fi
ning random: things like birthday may not be completely
random in a formal sense 32
33. Block randomization
https://egap.org/resource/10-things-to-know-about-randomization/
• It is possible, when randomizing, to specify the balance of particular
factors you care about between treatment and control groups
• even though it is not possible to specify which particular units are
selected for either group
• For example, you can specify that treatment and control groups
contain equal ratios of men to women
33
34. Block randomization
https://egap.org/resource/10-things-to-know-about-randomization/
• Why is this desirable?
• Not because our estimate of the average treatment e
ff
ect would otherwise be
biased, but because it could be really noisy.
• Suppose that a random assignment happened to generate a very male
treatment group and a very female control group. We would observe a
correlation between gender and treatment status. If we were to estimate a
treatment e
ff
ect, that treatment e
ff
ect would still be unbiased because gender
did not cause treatment status.
• However, it would be more di
ffi
cult to reject the null hypothesis that it was
not our treatment but gender that was producing the e
ff
ect.
• In short, the imbalance produces a noisy estimate, which makes it more
di
ffi
cult for us to be con
fi
dent in our estimates.
34
35. Block randomization
https://cran.r-project.org/web/packages/randomizr/vignettes/randomizr_vignette.html
• “Block random assignment (sometimes known as strati
fi
ed
random assignment) is a powerful tool when used well.
• In this design, subjects are sorted into blocks (strata) according to
their pre-treatment covariates, and then complete random
assignment is conducted within each block.
• For example, a researcher might block on gender, assigning
exactly half of the men and exactly half of the women to
treatment.”
35
36. Block randomization
https://cran.r-project.org/web/packages/randomizr/vignettes/randomizr_vignette.html
• “Why block?
• The
fi
rst reason is to signal to future readers that treatment e
ff
ect
heterogeneity may be of interest: is the treatment e
ff
ect di
ff
erent for
men versus women? Of course, such heterogeneity could be explored
if complete random assignment had been used, but blocking on a
covariate defends a researcher (somewhat) against claims of data
dredging.
• The second reason is to increase precision. If the blocking variables
are predictive of the outcome (i.e., they are correlated with the
outcome), then blocking may help to decrease sampling variability. It’s
important, however, not to overstate these advantages. The gains from
a blocked design can often be realized through covariate adjustment
alone.” 36
38. Cluster randomization
https://cran.r-project.org/web/packages/randomizr/vignettes/randomizr_vignette.html
• Assigning units to treatment or control as a cluster
• “Housemates in households: whole households are assigned to treatment or control
• Students in classrooms: whole classrooms are assigned to treatment or control
• Residents in towns or villages: whole communities are assigned to treatment or
control”
• Don’t do this unless you really have to!
• “Clustered assignment decreases the e
ff
ective sample size of an experiment. In
the extreme case when outcomes are perfectly correlated with clusters, the
experiment has an e
ff
ective sample size equal to the number of clusters. When
outcomes are perfectly uncorrelated with clusters, the e
ff
ective sample size is equal
to the number of subjects. Almost all cluster-assigned experiments fall somewhere in
the middle of these two extremes.”
38
40. Experiment cookbook
Druckman p.234+
• Big picture idea
• Short (i.e., few pages) document on the general topic and why it is
relevant to understanding social, political, and/or economic
phenomena
40
41. • Detailed literature review
• An exhaustive search of research on the topic, and detailed
descriptions of speci
fi
c studies
• It is here that the researcher should identify speci
fi
c gaps in
existing knowledge.
41
Experiment cookbook
Druckman p.234+
42. • Research question(s) and outcomes
• Given the identi
fi
cation of a gap in existing work, the next step is to
put forth a speci
fi
c question (or questions) to be addressed
• This includes identifying the precise outcome variable(s) of interest
42
Experiment cookbook
Druckman p.234+
43. • Theory and hypotheses
• Development of a theory and hypotheses to be tested
• Researchers should take their time to derive concrete and speci
fi
c
predictions
• As part of this step, potential mediators and/or moderators should
be speci
fi
ed
• Also, in putting forth predictions, one must be careful to isolate the
comparisons to be used.
43
Experiment cookbook
Druckman p.234+
44. • Research design
• Discussion of the designs used by others who have addressed
similar questions, and how the proposed design connects with
previous work. In many cases, the ideal strategy is to utilize and
extend prior designs.
• Discussion of how such a design will provide data relevant to the
larger questions.
44
Experiment cookbook
Druckman p.234+
45. • Research design (cont’d)
• Identifying where the data will come from, which includes:
• Consideration of the sample and any potential biases.
• Detailed measures and where the measures were obtained—that
is, where have they been used in prior studies? The measures
need to clearly connect to the hypotheses, including the
outcome variables and mediators/moderators.
45
Experiment cookbook
Druckman p.234+
46. • Research design (continued more)
• In many cases, the design may be too practically complex (e.g.,
number of experimental conditions relative to realistic sample size),
and decisions must be made on what can be trimmed without
interfering with the goal of the study.
• For original data collection, pre-tests of stimuli, question wordings,
etc., are critical to ensure the approach has content and construct
validity.
• Issues related to internal and external validity should be discussed.
46
Experiment cookbook
Druckman p.234+
47. • Data collection document
• If the project involves original data collection, a step-by-step plan
needs to be put forth so as not to later forget such details as
recruitment, implementation, etc.
47
Experiment cookbook
Druckman p.234+
48. • Data analysis plan
• There needs to be a clear data analysis plan—how exactly will the
data be used to test hypotheses? The researcher should directly
connect the design and measures to the hypotheses.
• This often involves making a table with each measure and how it
maps on to speci
fi
c hypotheses.
48
Experiment cookbook
Druckman p.234+
49. • Then
• Do the experiment
49
Experiment cookbook
Druckman p.234+
50. Next time
• More on speci
fi
c experimental designs
• Take a look at the readings — choose chapters that are interesting to
you
• Assignment 1!
• Due Sunday
50