This document provides an overview of research aptitude topics covered in Goalfinder Classes for the CBSE NET 2016 Paper 1 exam. It discusses key concepts in research methodology including exploratory research, variables, hypotheses, sampling methods, data collection techniques, research designs, reliability and validity. The document also lists various statistical analyses covered like ANOVA, correlation, factor analysis and experimental designs. It aims to help students prepare for questions related to research methodology and data interpretation in the CBSE NET exam.
This document provides an overview of research aptitude and methodology. It discusses what research is, its key characteristics, aims and objectives. It outlines different types of research including fundamental, applied, and action research. The document also details various research requirements and the steps involved in conducting research, from formulating the problem to collecting and analyzing data, developing hypotheses, and preparing the final report. Finally, it discusses different methods of research with a focus on the experimental method.
This document discusses qualitative research methods and mixing methods approaches. It begins by defining different qualitative research types like case studies, grounded theory, phenomenology, and ethnography. It then discusses multi-strategy research, noting both advantages like breaking down qual-quant divides, but also difficulties integrating methods from different epistemological perspectives. The document outlines arguments for and against mixing methods and different versions of the debate. It also discusses triangulation strategies and other mixed methods approaches like sequential or concurrent designs.
It’s based on descriptive data that does not make (regular) use of statistical procedures.
Study things in their natural settings, attempting to make sense of, or interpret, phenomena in terms of the meanings people bring to them and associated with the quality of a thing or phenomenon, such as feel, taste, expertise, image, leadership, reputation.
− Qualitative aspects are abstract; they either do not require measurement or cannot be measured.
Characteristics of Qualitative Research
Rich description
Research questions
Few participants
Natural and holistic representation
Ernie perspectives
Cyclical and open-ended processes
Possible ideological orientations
6.2. GATHERING QUALITATIVE DATA
Ethnographies
Interviews
Diaries/journals
Case studies
Observational techniques
6.2.1. Ethnographies: Focuses on the group rather than on the individual, stresses the importance of situating the study within the larger sociocultural context
This document provides an overview of research aptitude and methodology. It defines research as a careful investigation or inquiry to discover new facts in any field of knowledge. Research aptitude is the ability to systematically examine a situation for developing theories. The document outlines the objectives, types, and steps of research. It discusses topics like literature review, variable identification, hypothesis formulation, research design, sampling, and data collection methods.
Research aptitude is an important part of the UGC NET examination training program. The document outlines key aspects of research including meaning, types, methods, and ethics. It discusses the research process from formulating the problem to preparing the final report. Descriptive and experimental methods are highlighted. Workshops/conferences are described as providing hands-on experience. Publication and checking progress are also mentioned.
This document discusses various research methods and objectives that can be achieved through research. It describes 8 main objectives: 1) categorize, 2) describe, 3) explain, 4) evaluate, 5) compare, 6) correlate, 7) predict, and 8) control. It also outlines different types of research methods including descriptive, comparative, correlational, causal comparative, experimental, case study, phenomenology, ethnography, grounded theory, and mixed methods. Finally, it discusses various research designs such as historical, descriptive, correlation, comparative, experimental, simulation, evaluation, action, and ethnological.
This document defines and discusses different types of hypotheses used in research. It begins by defining a hypothesis as an educated guess formulated to explain observed facts and guide further investigation. The main types discussed are:
1. Research hypotheses, which can be attributive (describing attributes), associative (relationships between variables), or causal (explaining cause and effect).
2. Null hypotheses, which state that no significant difference or relationship exists.
3. Question form hypotheses, used when the relationship between variables is unclear.
The document also lists characteristics of a good hypothesis, importance of hypotheses, sources of hypotheses, and difficulties in formulating hypotheses.
This document provides an overview of research aptitude and methodology. It discusses what research is, its key characteristics, aims and objectives. It outlines different types of research including fundamental, applied, and action research. The document also details various research requirements and the steps involved in conducting research, from formulating the problem to collecting and analyzing data, developing hypotheses, and preparing the final report. Finally, it discusses different methods of research with a focus on the experimental method.
This document discusses qualitative research methods and mixing methods approaches. It begins by defining different qualitative research types like case studies, grounded theory, phenomenology, and ethnography. It then discusses multi-strategy research, noting both advantages like breaking down qual-quant divides, but also difficulties integrating methods from different epistemological perspectives. The document outlines arguments for and against mixing methods and different versions of the debate. It also discusses triangulation strategies and other mixed methods approaches like sequential or concurrent designs.
It’s based on descriptive data that does not make (regular) use of statistical procedures.
Study things in their natural settings, attempting to make sense of, or interpret, phenomena in terms of the meanings people bring to them and associated with the quality of a thing or phenomenon, such as feel, taste, expertise, image, leadership, reputation.
− Qualitative aspects are abstract; they either do not require measurement or cannot be measured.
Characteristics of Qualitative Research
Rich description
Research questions
Few participants
Natural and holistic representation
Ernie perspectives
Cyclical and open-ended processes
Possible ideological orientations
6.2. GATHERING QUALITATIVE DATA
Ethnographies
Interviews
Diaries/journals
Case studies
Observational techniques
6.2.1. Ethnographies: Focuses on the group rather than on the individual, stresses the importance of situating the study within the larger sociocultural context
This document provides an overview of research aptitude and methodology. It defines research as a careful investigation or inquiry to discover new facts in any field of knowledge. Research aptitude is the ability to systematically examine a situation for developing theories. The document outlines the objectives, types, and steps of research. It discusses topics like literature review, variable identification, hypothesis formulation, research design, sampling, and data collection methods.
Research aptitude is an important part of the UGC NET examination training program. The document outlines key aspects of research including meaning, types, methods, and ethics. It discusses the research process from formulating the problem to preparing the final report. Descriptive and experimental methods are highlighted. Workshops/conferences are described as providing hands-on experience. Publication and checking progress are also mentioned.
This document discusses various research methods and objectives that can be achieved through research. It describes 8 main objectives: 1) categorize, 2) describe, 3) explain, 4) evaluate, 5) compare, 6) correlate, 7) predict, and 8) control. It also outlines different types of research methods including descriptive, comparative, correlational, causal comparative, experimental, case study, phenomenology, ethnography, grounded theory, and mixed methods. Finally, it discusses various research designs such as historical, descriptive, correlation, comparative, experimental, simulation, evaluation, action, and ethnological.
This document defines and discusses different types of hypotheses used in research. It begins by defining a hypothesis as an educated guess formulated to explain observed facts and guide further investigation. The main types discussed are:
1. Research hypotheses, which can be attributive (describing attributes), associative (relationships between variables), or causal (explaining cause and effect).
2. Null hypotheses, which state that no significant difference or relationship exists.
3. Question form hypotheses, used when the relationship between variables is unclear.
The document also lists characteristics of a good hypothesis, importance of hypotheses, sources of hypotheses, and difficulties in formulating hypotheses.
CASE STUDY RESEARCH: DEVELOPMENTAL RESEARCH Erin Qing
1) A case study is an intensive analysis of an individual unit such as a person, group, or event that examines developmental factors in relation to context.
2) The study analyzed changes in Indonesian junior high school students' English learning motivation through questionnaires, interviews with a select group of students, and classroom observations.
3) Results found students' attitudes towards the long-term benefits of English were stable, but attitudes toward learning situations declined, with criticism of teaching methods.
This document discusses different types of classroom research methods: psychometric tradition, naturalistic inquiry, and action research. It provides details on what each method studies, similarities and differences between the methods, examples of research questions that would fit each method, and key issues researchers may want to investigate in classrooms. The document also discusses the role of objectivity and subjectivity in research, arguing that both have a place when researching human behaviors and experiences in educational contexts.
This document provides information on educational research. It begins with an introduction to research, noting that research purifies life and shows how to solve problems scientifically. It then lists the objectives of educational research as explaining concepts, describing scope, stating purposes, and differentiating between types of research. The document discusses sources of knowledge acquisition like learned authority and tradition. It states that educational research aims to develop effective methods for educators to achieve their goals. The document also outlines levels of education research, defines experimental and case study research, and discusses patents, including the criteria of patentability, tools for patent search, and the need for patents. It concludes by stating that research objectives should be clear, achievable questions or statements to answer the overall research problem
1) The document discusses key concepts in understanding research in second language learning, including formulating research questions and hypotheses, different types of sampling methods, and determining statistical significance.
2) It explains how to identify problems, operationalize variables, and develop testable hypotheses. Random sampling, systematic sampling, and stratified random sampling are sampling methods covered.
3) The passage also discusses statistical decisions like choosing appropriate tests, formulating statistical hypotheses, setting the alpha level, and determining whether to reject the null hypothesis based on p-values and significance levels. Key considerations like observed statistics, assumptions, and degrees of freedom are also addressed.
This document defines key terms related to theoretical and conceptual frameworks, including concepts, constructs, variables, conceptual framework, and theoretical framework. It explains that a conceptual framework consists of concepts and proposed relationships between concepts, while a theoretical framework is based on existing theories. The purposes of conceptual and theoretical frameworks are to clarify concepts, propose relationships between concepts, provide context for interpreting findings, and stimulate further research and theory development.
The document discusses different types of research including descriptive research, exploratory research, quantitative research, and qualitative research. Descriptive research involves collecting quantitative or qualitative data to describe categories of information. Exploratory research examines a subject to gain further insight and identify issues for future research without seeking definitive answers. Quantitative research relies on quantitative data and statistics while qualitative research relies on qualitative data like interviews and observations to understand concepts, beliefs, and experiences. Examples of different types of research studies are provided.
This document discusses key concepts in research methods. It defines what constitutes a science, including being based on empirical evidence, being objective and falsifiable. It also discusses peer review which ensures research quality, and some of its limitations. Different research designs are examined like experiments, observations and surveys. Ethical issues in research and ways to address them are outlined. The document also covers reliability and validity, important considerations in research quality. Sampling methods and their pros and cons are defined. Finally, it provides guidance on how to structure answers when discussing research methods concepts or studies.
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.
I. The document discusses various topics related to research including definitions of research, characteristics of research, purposes and aims of research, branches of research including qualitative vs. quantitative and applied vs. fundamental research.
II. It also discusses different methods of acquiring knowledge and the differences between qualitative and quantitative research methods.
III. Qualitative research is concerned with qualitative phenomena and seeks understanding, while quantitative research uses statistical measurement and seeks explanation and control.
The document discusses different methods used in architectural research including theoretical, interpretative, experimental, survey, simulation, qualitative, and action research. It provides an overview of the key aspects of each method including their ontological and epistemological assumptions, disciplinary base, research goals, methodological orientation, key methodological concepts, variables, data analysis techniques, the participant and researcher roles, and whether political pressures are included or ignored. The different research methods range from curiosity-oriented theoretical research to mission-oriented action research focused on practical solutions.
This document discusses research problems and types of educational research. It begins by defining a research problem as an area of concern, condition to be improved, or troubling question that requires investigation. The purpose of a research problem is to introduce importance, place the problem in context, and provide a framework for reporting results.
The document then discusses three main types of educational research: historical research which investigates past events; descriptive research which describes current conditions without manipulation; and experimental research which manipulates and examines the effects of variables. Descriptive research includes field studies, ex-post-facto research, survey research, content analysis, and case studies. Key aspects and limitations of each type are outlined. Criteria for a good
This document outlines the key components and processes of conducting research. It discusses defining research problems and objectives, developing hypotheses, reviewing related literature, choosing appropriate research designs (such as descriptive, experimental, correlational), determining sample sizes and sampling methods, collecting and analyzing data, and presenting findings. It also covers important concepts like validity, reliability, and operationalizing definitions. The overall purpose is to provide guidance to researchers on how to properly plan and carry out a study.
This document provides an overview of research methodology. It discusses key concepts such as the meaning of research, objectives of research, types of research including descriptive vs analytical and quantitative vs qualitative, and significance of research. The main types of research covered are descriptive research which aims to describe the current state, analytical research which evaluates facts to make a critical assessment, applied research which aims to solve practical problems, and fundamental research which adds to the body of scientific knowledge. Quantitative research is based on measurement while qualitative research investigates underlying reasons for behaviors.
This document provides guidance on conducting quantitative research. It explains that quantitative research involves surveying large numbers of people in a structured way to collect numerical data and statistics. It is important to use a representative sample of the target population to obtain reliable results. The overall goal is to objectively and systematically obtain information about the world through numerical data.
TSL3133 Topic 3 Introduction to Various Types of Educational Research DesignYee Bee Choo
This document discusses different types of quantitative and qualitative research design. It provides details on experimental, quasi-experimental, survey, and correlational research designs under quantitative research. For qualitative research, it discusses ethnography, case study, historical, and narrative research. It provides advantages and disadvantages of both quantitative and qualitative research. For experimental design specifically, it describes independent and dependent variables, and control and experimental groups.
Research is a systematic inquiry to describe, explain, predict and control the observed phenomenon. Research involves inductive and deductive methods (Babbie, 1998). Inductive methods analyze the observed phenomenon and identify the general principles, structures, or processes underlying the phenomenon observed; deductive methods verify the hypothesized principles through observations. The purposes are different: one is to develop explanations, and the other is to test the validity of the explanations.
This document provides an overview of research methodologies. It defines research as a systematic investigation to discover and revise facts. The objectives of research are to gain new insights, accurately describe phenomena, determine relationships between variables, and test hypotheses. Research can be descriptive, analytical, applied, fundamental, quantitative, qualitative, conceptual, or empirical. The significance of research is that it leads to progress, promotes logical thinking, and helps address business, economic, social and policy issues.
This document provides an overview of research methodology. It discusses that research methodology is the systematic process of solving a research problem. It involves understanding which research methods and techniques are applicable to specific problems. The chapter then describes the procedural aspects used in the research process, including research philosophy, philosophical worldviews, research approach, research design, data collection strategies, data analysis, and ethical considerations. It presents the figure showing the methodological structure of research. Finally, it discusses various philosophical worldviews including postpositivism that guide researchers in determining the appropriate research design based on the research question.
Research is defined as a systematic effort to gain new knowledge. It involves formulating a research problem, conducting a literature review, developing hypotheses, designing a study, collecting and analyzing data, and reporting findings. The goal of research is to discover answers to questions through objective and systematic methods of finding solutions.
CASE STUDY RESEARCH: DEVELOPMENTAL RESEARCH Erin Qing
1) A case study is an intensive analysis of an individual unit such as a person, group, or event that examines developmental factors in relation to context.
2) The study analyzed changes in Indonesian junior high school students' English learning motivation through questionnaires, interviews with a select group of students, and classroom observations.
3) Results found students' attitudes towards the long-term benefits of English were stable, but attitudes toward learning situations declined, with criticism of teaching methods.
This document discusses different types of classroom research methods: psychometric tradition, naturalistic inquiry, and action research. It provides details on what each method studies, similarities and differences between the methods, examples of research questions that would fit each method, and key issues researchers may want to investigate in classrooms. The document also discusses the role of objectivity and subjectivity in research, arguing that both have a place when researching human behaviors and experiences in educational contexts.
This document provides information on educational research. It begins with an introduction to research, noting that research purifies life and shows how to solve problems scientifically. It then lists the objectives of educational research as explaining concepts, describing scope, stating purposes, and differentiating between types of research. The document discusses sources of knowledge acquisition like learned authority and tradition. It states that educational research aims to develop effective methods for educators to achieve their goals. The document also outlines levels of education research, defines experimental and case study research, and discusses patents, including the criteria of patentability, tools for patent search, and the need for patents. It concludes by stating that research objectives should be clear, achievable questions or statements to answer the overall research problem
1) The document discusses key concepts in understanding research in second language learning, including formulating research questions and hypotheses, different types of sampling methods, and determining statistical significance.
2) It explains how to identify problems, operationalize variables, and develop testable hypotheses. Random sampling, systematic sampling, and stratified random sampling are sampling methods covered.
3) The passage also discusses statistical decisions like choosing appropriate tests, formulating statistical hypotheses, setting the alpha level, and determining whether to reject the null hypothesis based on p-values and significance levels. Key considerations like observed statistics, assumptions, and degrees of freedom are also addressed.
This document defines key terms related to theoretical and conceptual frameworks, including concepts, constructs, variables, conceptual framework, and theoretical framework. It explains that a conceptual framework consists of concepts and proposed relationships between concepts, while a theoretical framework is based on existing theories. The purposes of conceptual and theoretical frameworks are to clarify concepts, propose relationships between concepts, provide context for interpreting findings, and stimulate further research and theory development.
The document discusses different types of research including descriptive research, exploratory research, quantitative research, and qualitative research. Descriptive research involves collecting quantitative or qualitative data to describe categories of information. Exploratory research examines a subject to gain further insight and identify issues for future research without seeking definitive answers. Quantitative research relies on quantitative data and statistics while qualitative research relies on qualitative data like interviews and observations to understand concepts, beliefs, and experiences. Examples of different types of research studies are provided.
This document discusses key concepts in research methods. It defines what constitutes a science, including being based on empirical evidence, being objective and falsifiable. It also discusses peer review which ensures research quality, and some of its limitations. Different research designs are examined like experiments, observations and surveys. Ethical issues in research and ways to address them are outlined. The document also covers reliability and validity, important considerations in research quality. Sampling methods and their pros and cons are defined. Finally, it provides guidance on how to structure answers when discussing research methods concepts or studies.
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.
I. The document discusses various topics related to research including definitions of research, characteristics of research, purposes and aims of research, branches of research including qualitative vs. quantitative and applied vs. fundamental research.
II. It also discusses different methods of acquiring knowledge and the differences between qualitative and quantitative research methods.
III. Qualitative research is concerned with qualitative phenomena and seeks understanding, while quantitative research uses statistical measurement and seeks explanation and control.
The document discusses different methods used in architectural research including theoretical, interpretative, experimental, survey, simulation, qualitative, and action research. It provides an overview of the key aspects of each method including their ontological and epistemological assumptions, disciplinary base, research goals, methodological orientation, key methodological concepts, variables, data analysis techniques, the participant and researcher roles, and whether political pressures are included or ignored. The different research methods range from curiosity-oriented theoretical research to mission-oriented action research focused on practical solutions.
This document discusses research problems and types of educational research. It begins by defining a research problem as an area of concern, condition to be improved, or troubling question that requires investigation. The purpose of a research problem is to introduce importance, place the problem in context, and provide a framework for reporting results.
The document then discusses three main types of educational research: historical research which investigates past events; descriptive research which describes current conditions without manipulation; and experimental research which manipulates and examines the effects of variables. Descriptive research includes field studies, ex-post-facto research, survey research, content analysis, and case studies. Key aspects and limitations of each type are outlined. Criteria for a good
This document outlines the key components and processes of conducting research. It discusses defining research problems and objectives, developing hypotheses, reviewing related literature, choosing appropriate research designs (such as descriptive, experimental, correlational), determining sample sizes and sampling methods, collecting and analyzing data, and presenting findings. It also covers important concepts like validity, reliability, and operationalizing definitions. The overall purpose is to provide guidance to researchers on how to properly plan and carry out a study.
This document provides an overview of research methodology. It discusses key concepts such as the meaning of research, objectives of research, types of research including descriptive vs analytical and quantitative vs qualitative, and significance of research. The main types of research covered are descriptive research which aims to describe the current state, analytical research which evaluates facts to make a critical assessment, applied research which aims to solve practical problems, and fundamental research which adds to the body of scientific knowledge. Quantitative research is based on measurement while qualitative research investigates underlying reasons for behaviors.
This document provides guidance on conducting quantitative research. It explains that quantitative research involves surveying large numbers of people in a structured way to collect numerical data and statistics. It is important to use a representative sample of the target population to obtain reliable results. The overall goal is to objectively and systematically obtain information about the world through numerical data.
TSL3133 Topic 3 Introduction to Various Types of Educational Research DesignYee Bee Choo
This document discusses different types of quantitative and qualitative research design. It provides details on experimental, quasi-experimental, survey, and correlational research designs under quantitative research. For qualitative research, it discusses ethnography, case study, historical, and narrative research. It provides advantages and disadvantages of both quantitative and qualitative research. For experimental design specifically, it describes independent and dependent variables, and control and experimental groups.
Research is a systematic inquiry to describe, explain, predict and control the observed phenomenon. Research involves inductive and deductive methods (Babbie, 1998). Inductive methods analyze the observed phenomenon and identify the general principles, structures, or processes underlying the phenomenon observed; deductive methods verify the hypothesized principles through observations. The purposes are different: one is to develop explanations, and the other is to test the validity of the explanations.
This document provides an overview of research methodologies. It defines research as a systematic investigation to discover and revise facts. The objectives of research are to gain new insights, accurately describe phenomena, determine relationships between variables, and test hypotheses. Research can be descriptive, analytical, applied, fundamental, quantitative, qualitative, conceptual, or empirical. The significance of research is that it leads to progress, promotes logical thinking, and helps address business, economic, social and policy issues.
This document provides an overview of research methodology. It discusses that research methodology is the systematic process of solving a research problem. It involves understanding which research methods and techniques are applicable to specific problems. The chapter then describes the procedural aspects used in the research process, including research philosophy, philosophical worldviews, research approach, research design, data collection strategies, data analysis, and ethical considerations. It presents the figure showing the methodological structure of research. Finally, it discusses various philosophical worldviews including postpositivism that guide researchers in determining the appropriate research design based on the research question.
Research is defined as a systematic effort to gain new knowledge. It involves formulating a research problem, conducting a literature review, developing hypotheses, designing a study, collecting and analyzing data, and reporting findings. The goal of research is to discover answers to questions through objective and systematic methods of finding solutions.
This document provides an overview of hypotheses for a presentation. It begins with learning outcomes which are to explain the meaning and significance of hypotheses, identify types of hypotheses, and illustrate why hypotheses are needed.
The presentation will cover the scientific method, meaning and types of variables, characteristics of good hypotheses, categories of hypotheses including null and alternative, and how to form and test hypotheses. Hypotheses are defined as educated guesses that relate variables and guide research. They must be testable, falsifiable, and contribute to theory. Hypotheses can be categorized by their formulation as null or alternative, by direction as directional or non-directional, and by their derivation as inductive or deductive.
This document provides an overview of hypotheses in research methodology. It defines a hypothesis as a tentative explanation or educated guess about a research problem or outcome. There are several types of hypotheses, including research hypotheses (simple or complex), directional vs. non-directional, associative vs. causal, statistical vs. null hypotheses. Variables are also defined, including independent and dependent variables. Formulating a strong hypothesis requires an understanding of the topic area and existing research findings. Overall, hypotheses help focus research and provide a framework for analyzing results.
The document discusses different categories of research including:
- By type (primary vs secondary research)
- By objective (qualitative, quantitative, mixed methods)
- By form (exploratory, constructive, empirical research)
- By reasoning (deductive vs inductive reasoning)
It also briefly outlines four main research paradigms: postpositivism, social constructivism, advocacy/participatory, and pragmatism.
Here are the key elements of a research methodology chapter:
1. Research Design
- Describe the overall research design and approach. Is it qualitative, quantitative, or mixed methods?
- Provide rationale for chosen design.
2. Data Collection Methods
- Describe specific methods for collecting primary data, e.g. surveys, interviews, experiments.
- Include details on instrument design, sampling approach, sample size.
3. Data Analysis Methods
- Describe how collected data will be analyzed both qualitatively and quantitatively
- Cite specific analytical techniques, e.g. thematic analysis, regression analysis
4. Validity and Reliability
- Discuss strategies for ensuring validity of
There are several considerations when selecting a research topic, including academic/intellectual factors and practical applicability. Students may choose from assigned topics, field study topics using various resources, or free choice topics based on their own interests. Key factors in topic selection include the researcher's ability to study the topic thoroughly, available resources and techniques, and the topic's relevance to existing theories. Formulating a research problem involves discovering an issue in need of study and narrowing it to a manageable size. Developing testable hypotheses, clearly defining concepts, and establishing operational definitions allows relating findings to broader knowledge.
This document discusses different types of research. It defines research and describes several classifications of research including:
- Descriptive research which aims to describe characteristics of individuals, situations, or groups.
- Analytical research which analyzes existing facts and information to critically evaluate material.
- Applied research which aims to solve practical problems, versus fundamental research which adds to scientific knowledge.
- Quantitative research which measures quantity/amount versus qualitative research involving quality/kind such as motivation.
- Conceptual research related to abstract ideas versus empirical research based on observation and experimentation.
- A hypothesis is a tentative statement about the solution to a problem that can be tested and verified. It predicts the relationship between two or more variables.
- A good hypothesis is based on existing knowledge, states a clear relationship between variables, and allows for testing and verification.
- Developing a hypothesis involves asking a research question, conducting preliminary research, and formulating a statement about the expected relationship between variables to be tested. Testing a hypothesis aims to determine if it is supported by evidence but does not prove it definitively.
7 HYPOTHETICALS AND YOU TESTING YOUR QUESTIONS7 MEDIA LIBRARY.docxtaishao1
7 HYPOTHETICALS AND YOU TESTING YOUR QUESTIONS
7: MEDIA LIBRARY
Premium Videos
Core Concepts in Stats Video
· Probability and Hypothesis Testing
Lightboard Lecture Video
· Hypothesis Testing
Difficulty Scale
(don’t plan on going out tonight)
WHAT YOU WILL LEARN IN THIS CHAPTER
· Understanding the difference between a sample and a population
· Understanding the importance of the null and research hypotheses
· Using criteria to judge a good hypothesis
SO YOU WANT TO BE A SCIENTIST
You might have heard the term hypothesis used in other classes. You may even have had to formulate one for a research project you did for another class, or you may have read one or two in a journal article. If so, then you probably have a good idea what a hypothesis is. For those of you who are unfamiliar with this often-used term, a hypothesis is basically “an educated guess.” Its most important role is to reflect the general problem statement or question that was the motivation for asking the research question in the first place.
That’s why taking the care and time to formulate a really precise and clear research question is so important. This research question will guide your creation of a hypothesis, and in turn, the hypothesis will determine the techniques you will use to test it and answer the question that was originally asked.
So, a good hypothesis translates a problem statement or a research question into a format that makes it easier to examine. This format is called a hypothesis. We will talk about what makes a hypothesis a good one later in this chapter. Before that, let’s turn our attention to the difference between a sample and a population. This is an important distinction, because while hypotheses usually describe a population, hypothesis testing deals with a sample and then the results are generalized to the larger population. We also address the two main types of hypotheses (the null hypothesis and the research hypothesis). But first, let’s formally define some simple terms that we have used earlier in Statistics for People Who (Think They) Hate Statistics.
SAMPLES AND POPULATIONS
As a good scientist, you would like to be able to say that if Method A is better than Method B in your study, this is true forever and always and for all people in the universe, right? Indeed. And, if you do enough research on the relative merits of Methods A and B and test enough people, you may someday be able to say that.
But don’t get too excited, because it’s unlikely you will ever be able to speak with such confidence. It takes too much money ($$$) and too much time (all those people!) to do all that research, and besides, it’s not even necessary. Instead, you can just select a representative sample from the population and test your hypothesis about the relative merits of Methods A and B on that sample.
Given the constraints of never enough time and never enough research funds, with which almost all scientists live, the next best strategy is to take a portion of a lar.
7 HYPOTHETICALS AND YOU TESTING YOUR QUESTIONS7 MEDIA LIBRARY.docxevonnehoggarth79783
7 HYPOTHETICALS AND YOU TESTING YOUR QUESTIONS
7: MEDIA LIBRARY
Premium Videos
Core Concepts in Stats Video
· Probability and Hypothesis Testing
Lightboard Lecture Video
· Hypothesis Testing
Difficulty Scale
(don’t plan on going out tonight)
WHAT YOU WILL LEARN IN THIS CHAPTER
· Understanding the difference between a sample and a population
· Understanding the importance of the null and research hypotheses
· Using criteria to judge a good hypothesis
SO YOU WANT TO BE A SCIENTIST
You might have heard the term hypothesis used in other classes. You may even have had to formulate one for a research project you did for another class, or you may have read one or two in a journal article. If so, then you probably have a good idea what a hypothesis is. For those of you who are unfamiliar with this often-used term, a hypothesis is basically “an educated guess.” Its most important role is to reflect the general problem statement or question that was the motivation for asking the research question in the first place.
That’s why taking the care and time to formulate a really precise and clear research question is so important. This research question will guide your creation of a hypothesis, and in turn, the hypothesis will determine the techniques you will use to test it and answer the question that was originally asked.
So, a good hypothesis translates a problem statement or a research question into a format that makes it easier to examine. This format is called a hypothesis. We will talk about what makes a hypothesis a good one later in this chapter. Before that, let’s turn our attention to the difference between a sample and a population. This is an important distinction, because while hypotheses usually describe a population, hypothesis testing deals with a sample and then the results are generalized to the larger population. We also address the two main types of hypotheses (the null hypothesis and the research hypothesis). But first, let’s formally define some simple terms that we have used earlier in Statistics for People Who (Think They) Hate Statistics.
SAMPLES AND POPULATIONS
As a good scientist, you would like to be able to say that if Method A is better than Method B in your study, this is true forever and always and for all people in the universe, right? Indeed. And, if you do enough research on the relative merits of Methods A and B and test enough people, you may someday be able to say that.
But don’t get too excited, because it’s unlikely you will ever be able to speak with such confidence. It takes too much money ($$$) and too much time (all those people!) to do all that research, and besides, it’s not even necessary. Instead, you can just select a representative sample from the population and test your hypothesis about the relative merits of Methods A and B on that sample.
Given the constraints of never enough time and never enough research funds, with which almost all scientists live, the next best strategy is to take a portion of a lar.
The document provides an overview of psychological research methods. It defines research as systematic inquiry aimed at understanding human behavior and mental processes. Various research methods are described, including experimental, quasi-experimental, and non-experimental designs. Key aspects of the research process like developing hypotheses, collecting both qualitative and quantitative data, ensuring reliability and validity, and addressing ethical considerations are summarized.
This document discusses different dimensions for characterizing research projects, including topic, novelty, technology, scope, mode, methods, ideology, politics, and utility. It provides examples of different types of projects that fall under each dimension, such as observational vs. interventionist studies. The document emphasizes that research projects can be understood as existing in a multidimensional space defined by these dimensions, and that considering all relevant dimensions is important for designing and conducting a high-quality project.
The document discusses key elements and steps of the research process. It begins by defining research and different types of research problems. It then outlines the seven steps of the research process: 1) identifying a research problem, 2) formulating a hypothesis, 3) reviewing related literature, 4) preparing a research design, 5) conducting actual experimentation, 6) analyzing results and discussion, and 7) formulating conclusions and recommendations. The document also discusses types of research including exploratory, descriptive, and causal research. It concludes by outlining key elements that should be included in any research paper such as an abstract, introduction, literature review, methodology, body, results, discussion, conclusion, and citations.
The document provides an overview of exploratory research and descriptive research. It defines exploratory research as research used to investigate problems that are not clearly defined in order to better understand the problem but not provide conclusive results. Descriptive research aims to accurately describe populations, situations, or phenomena. The document outlines the characteristics, methods, advantages, and disadvantages of both exploratory and descriptive research.
The document discusses various topics related to research methodology including definitions of research, types of research, research methods, sampling techniques, data collection methods, and experimental research. Some key points:
- Research is defined as a systematic effort to gain new knowledge through objective and scientific methods. It involves identifying a problem, formulating a hypothesis, collecting and analyzing data, and reporting findings.
- There are different types of research including descriptive, analytical, applied, fundamental, quantitative, qualitative, and more. Research methods can be quantitative, qualitative, experimental, case study, etc.
- Important steps in research include formulating the problem, literature review, developing hypotheses, research design, sampling, data collection, analysis, testing hypotheses,
Qualitative Research Methods Essay
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8
More Components: Knowledge, Literature, Intellectual Projects
Keywords
action; critical evaluation; instrumentalism; intellectual projects; knowledge; literature; policy; practice; reflexive action; research; theory; understanding; value stances
In the last two chapters, we first introduced the idea of a mental map for navigating the literature plus the tools for thinking that represent the key to this map. We then looked at the first map component: the two dimensions of variation amongst knowledge claims. Here we complete our introduction to the mental map by describing its other three components:
three
kinds of knowledge
that are generated by reflecting on, investigating and taking action in the social world;
four
types of literature
that inform understanding and practice;
five
sorts of intellectual project
that generate literature about the social world.
Figure 8.1 Tools for thinking and the creation of three kinds of knowledge about the social world
Three kinds of knowledge
The three kinds of knowledge that we distinguish are
theoretical
,
research
and
practice
. We describe each below and show how they relate to the set of tools for thinking summarized in
Chapter 6
.
Figure 8.1
represents that relationship, showing that the tools for thinking play a central role. They are employed both to generate and to question the three kinds of knowledge.
What is theoretical knowledge?
The tools for thinking are most obviously reflected in
theoretical knowledge
– you cannot have a theory without a set of connected concepts. We define theoretical knowledge as deriving from the creation or use of theory, in the following way. On the basis of a theory about the social world, we make claims to knowledge about what the social world is like. The theory itself may or may not be our own and will have been developed on the basis of patterns discerned in that social world, whether through general observation (armchair theorizing), through specific investigations (empirically based theorizing) or a mixture of the two.
For example, in order to provide warranting for the claim that all children should be given the chance to learn a foreign language before the age of eight, an author might offer as evidence the theoretical knowledge that there is a ‘critical period’ for language acquisition. The theory upon which the author is drawing for this knowledge has been built up over the years by various theorists (beginning with Eric Lenneberg). The theorists have used both general observation about what happens when people of different ages learn a language and a range of empirical studies that have sought to establish what the critical age and determining factors are. Bundled up in the theory are potential claims about roles for biology, environment and motivation. The author would need to unpack these roles if the fundamental claim were to be developed into an empirical research study (to see how well it worked to offer foreign langua ...
How Is Each Related To Deductive Inquiry?
Deduction Vs Deductive Reasoning
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A hypothesis is a prediction about the relationship between two variables that is tested through research. There are different types of hypotheses, including simple, complex, empirical, null, and alternative hypotheses. Researchers use hypothesis testing procedures to evaluate hypotheses based on sample data and either reject or fail to reject the null hypothesis. Type I and Type II errors can occur when evaluating hypotheses. Hypotheses help focus research, guide data collection, and allow conclusions to be drawn.
JLPT (Japanese Language Proficiency Test) LEVEL N5
online course, Useful For : Foundational course towards reaching N3 level, for basic Japanese Language conversational, reading and writing proficiency.
This document provides an overview of teaching aptitude and methods for evaluating teaching effectiveness. It discusses definitions of teaching, the nature and objectives of teaching, qualities of effective teachers, and learning domains. Methods of teaching covered include lectures, tutorials, classroom management, case studies, and brainstorming. Evaluation elements discussed are testing, measurement, and continuous and comprehensive evaluation. The document is from an online resource for teaching aptitude test preparation that provides study materials and practice questions.
Net set math logical reading comprehension aptitude for exams and interviews ...amitkuls
Mathematical Reasoning Number Series Letter and Symbol Series Coding and Decoding Classification: Odd Man Out Blood Relations Analogies Direction and Senses Artificial Language Permutation and Combination Logical Deductions - Syllogism Averages Seating Arrangement Venn Diagrams Problem on Ages Reading Comprehension Data Interpretation Speed Solving
Net set Information and Communication Technology (Computer Theory)amitkuls
Data Security Hardware Data Storage Storage Media & Devices File Structure Card Operating System Full duplex, Duplex, Full Half, Simplex Assembler and Disassembler GUI Operating System Network ETHERNET, TYPES, IPV , IPV ISP, DSL / ADSL, DNS Virtual Reality MOOC Virtual University
Types of communication, formal, informal, verbal, non-verbal, in an organization structure, johari window, shannon weaver model, David burlo, schramm model, Entropy and Redundancy, feedback in communication, transactional models in classroom, mass communication, channels of mass media feed-forward
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.
ISO/IEC 27001, ISO/IEC 42001, and GDPR: Best Practices for Implementation and...PECB
Denis is a dynamic and results-driven Chief Information Officer (CIO) with a distinguished career spanning information systems analysis and technical project management. With a proven track record of spearheading the design and delivery of cutting-edge Information Management solutions, he has consistently elevated business operations, streamlined reporting functions, and maximized process efficiency.
Certified as an ISO/IEC 27001: Information Security Management Systems (ISMS) Lead Implementer, Data Protection Officer, and Cyber Risks Analyst, Denis brings a heightened focus on data security, privacy, and cyber resilience to every endeavor.
His expertise extends across a diverse spectrum of reporting, database, and web development applications, underpinned by an exceptional grasp of data storage and virtualization technologies. His proficiency in application testing, database administration, and data cleansing ensures seamless execution of complex projects.
What sets Denis apart is his comprehensive understanding of Business and Systems Analysis technologies, honed through involvement in all phases of the Software Development Lifecycle (SDLC). From meticulous requirements gathering to precise analysis, innovative design, rigorous development, thorough testing, and successful implementation, he has consistently delivered exceptional results.
Throughout his career, he has taken on multifaceted roles, from leading technical project management teams to owning solutions that drive operational excellence. His conscientious and proactive approach is unwavering, whether he is working independently or collaboratively within a team. His ability to connect with colleagues on a personal level underscores his commitment to fostering a harmonious and productive workplace environment.
Date: May 29, 2024
Tags: Information Security, ISO/IEC 27001, ISO/IEC 42001, Artificial Intelligence, GDPR
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How to Make a Field Mandatory in Odoo 17Celine George
In Odoo, making a field required can be done through both Python code and XML views. When you set the required attribute to True in Python code, it makes the field required across all views where it's used. Conversely, when you set the required attribute in XML views, it makes the field required only in the context of that particular view.
বাংলাদেশের অর্থনৈতিক সমীক্ষা ২০২৪ [Bangladesh Economic Review 2024 Bangla.pdf] কম্পিউটার , ট্যাব ও স্মার্ট ফোন ভার্সন সহ সম্পূর্ণ বাংলা ই-বুক বা pdf বই " সুচিপত্র ...বুকমার্ক মেনু 🔖 ও হাইপার লিংক মেনু 📝👆 যুক্ত ..
আমাদের সবার জন্য খুব খুব গুরুত্বপূর্ণ একটি বই ..বিসিএস, ব্যাংক, ইউনিভার্সিটি ভর্তি ও যে কোন প্রতিযোগিতা মূলক পরীক্ষার জন্য এর খুব ইম্পরট্যান্ট একটি বিষয় ...তাছাড়া বাংলাদেশের সাম্প্রতিক যে কোন ডাটা বা তথ্য এই বইতে পাবেন ...
তাই একজন নাগরিক হিসাবে এই তথ্য গুলো আপনার জানা প্রয়োজন ...।
বিসিএস ও ব্যাংক এর লিখিত পরীক্ষা ...+এছাড়া মাধ্যমিক ও উচ্চমাধ্যমিকের স্টুডেন্টদের জন্য অনেক কাজে আসবে ...
A workshop hosted by the South African Journal of Science aimed at postgraduate students and early career researchers with little or no experience in writing and publishing journal articles.
Walmart Business+ and Spark Good for Nonprofits.pdfTechSoup
"Learn about all the ways Walmart supports nonprofit organizations.
You will hear from Liz Willett, the Head of Nonprofits, and hear about what Walmart is doing to help nonprofits, including Walmart Business and Spark Good. Walmart Business+ is a new offer for nonprofits that offers discounts and also streamlines nonprofits order and expense tracking, saving time and money.
The webinar may also give some examples on how nonprofits can best leverage Walmart Business+.
The event will cover the following::
Walmart Business + (https://business.walmart.com/plus) is a new shopping experience for nonprofits, schools, and local business customers that connects an exclusive online shopping experience to stores. Benefits include free delivery and shipping, a 'Spend Analytics” feature, special discounts, deals and tax-exempt shopping.
Special TechSoup offer for a free 180 days membership, and up to $150 in discounts on eligible orders.
Spark Good (walmart.com/sparkgood) is a charitable platform that enables nonprofits to receive donations directly from customers and associates.
Answers about how you can do more with Walmart!"
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.
This presentation was provided by Steph Pollock of The American Psychological Association’s Journals Program, and Damita Snow, of The American Society of Civil Engineers (ASCE), for the initial session of NISO's 2024 Training Series "DEIA in the Scholarly Landscape." Session One: 'Setting Expectations: a DEIA Primer,' was held June 6, 2024.
Main Java[All of the Base Concepts}.docxadhitya5119
This is part 1 of my Java Learning Journey. This Contains Custom methods, classes, constructors, packages, multithreading , try- catch block, finally block and more.
Leveraging Generative AI to Drive Nonprofit InnovationTechSoup
In this webinar, participants learned how to utilize Generative AI to streamline operations and elevate member engagement. Amazon Web Service experts provided a customer specific use cases and dived into low/no-code tools that are quick and easy to deploy through Amazon Web Service (AWS.)
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
1. Math Reasoning, Reading Comprehension, Data InterpretationGoalfinder Classes –
1
Goalfinder.com
Research Aptitude
Goalfinder Classes: CBSE NET 2016 - Paper 1
Total number of Pages: 185
Portion covered till CBSE NET December 2015
Classes
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Research Aptitude
Goalfinder Classes: CBSE NET 2016 - Paper 1
Table of Content
Aims and Objectives of Research
Hypotheses
Null hypothesis
Alternative Hypothesis
Significance, P-value, one tailed test etc.
Types of Research
Application
As per Objectives
Exploratory Research
Conclusive Research
Correlation Research
Explanatory (Causal / Experimental) Research
Comparison between exploratory, descriptive and causal
Experimentation and Market Testing
Type of Information Sought
Qualitative and Quantitative research
Other 10 types of Research Design
Data: Primary and Secondary Data
Data Collection and Method of study in research
Content analysis
Game or role-playing
Primary Market Research Method Quantitative
Experiments Quasi Experiment and Field Trials
Sociogram
Variable and their Types
Sampling Methods
a. Probability Sampling
1. Simple Random Sampling
2. Systematic Sampling:
3. Stratified random sampling
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4. Cluster Sampling
b. Non Probability Sampling
1. Convenience sampling
2. Purposive /Judgment Sampling
4. Snowball Sample
Types of Errors:
Measurement
Data Exploration
Univariate vs. Bivariate Data
Analysis of Variance (ANOVA)
Problem Solving
Central Tendency and Normal Distribution
Normal Distribution
Variance
Effect Size
Frequency distribution: Skewed, Mesokurtic, Leptokurtic, Platykurtic
Hypothesis Testing
"True" Mean and Confidence Interval
Margin of Error (Confidence Interval)
Type I errors and type II errors
One-Tailed and Two-Tailed Tests
Parametric and Non-parametric Tests
Bi- and Multivariate Inferential Statistical Tests (Parametric)
Chi Square
Degrees of freedom
T-test
Z-test and t-test
Analysis of Variance (ANOVA)
Correlation (measures relationships between two variables)
Factor analysis
Sign test
Run Test
Other data display methods
Experimental Design
Pre-Experimental Designs
Quasi experiment Design
True Experimental Design
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Research Aptitude
4. Classes Research AptitudeGoalfinder
Reliability and Validity
Validity
Research Requirements
Steps of Research
The Preliminary Section
Research Ethics
Seminar, Workshop, Conference, Symposium
Paper, Article
Quality of a research journal
Style Rules
Appendix : Research Methodology Diagram
APA Format
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Sample: Research Aptitude
Null hypothesis
The null hypothesis (H0) is a hypothesis which the researcher tries to disprove, reject or nullify. The 'null' often
refers to the common view of something, while the alternative hypothesis is what the researcher really thinks
is the cause of a phenomenon.
The null hypothesis is essentially the "devil's advocate" position. That is, it assumes that whatever you are
trying to prove did not happen (hint: it usually states that something equals zero). For example, the two
different teaching methods did not result in different exam performances (i.e., zero difference). Another
example might be that there is no relationship between anxiety and athletic performance (i.e., the slope is
zero). The alternative hypothesis states the opposite and is usually the hypothesis you are trying to prove (e.g.,
the two different teaching methods did result in different exam performances). Initially, you can state these
hypotheses in more general terms (e.g., using terms like "effect", "relationship", etc.).
The simplistic definition of the null is as the opposite of the alternative hypothesis, H1, although the principle is
a little more complex than that.
A researcher may postulate a hypothesis:
H1: Tomato plants exhibit a higher rate of growth when planted in compost rather than in soil.
And a null hypothesis:
H0: Tomato plants do not exhibit a higher rate of growth when planted in compost rather than soil.
It is important to carefully select the wording of the null, and ensure that it is as specific as possible. For
example, the researcher might postulate a null hypothesis:
H0: Tomato plants show no difference in growth rates when planted in compost rather than soil.
There is a major flaw with this H0. If the plants actually grow more slowly in compost than in soil, an impasse is
reached. H1 is not supported, but neither is H0, because there is a difference in growth rates.
If the null is rejected, with no alternative, the experiment may be invalid. This is the reason why science uses a
battery of deductive and inductive processes to ensure that there are no flaws in the hypotheses.
Many scientists neglect the null, assuming that it is merely the opposite of the alternative, but it is good
practice to spend a little time creating a sound hypothesis. It is not possible to change any hypothesis
retrospectively, including H0.
The first step in evaluating sample results is to set up a null hypothesis (Ho). The null hypothesis is a
hypothesis of no differences. We formulate it for the express purpose of rejecting it. It is formulated before we
collect the data (a priori). For example, we may wish to know whether a particular promotional campaign has
succeeded in increasing awareness amongst housewives of a certain brand of biscuit. Before the campaign we
have a certain measure of awareness, say x%. After the campaign we obtain another measure of the
awareness, say y%. The null hypothesis in this case would be that "there is no difference between the
proportions aware of the brand, before and after the campaign",
Since we are dealing with sample results, we would expect some differences; and we must try and establish
whether these differences are real (i.e. statistically significant) or whether they are due to random error or
chance.
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Exploratory Research
Exploratory research for discovering new ideas, understanding a problem, screening alternatives
• To develop initial hunches or insights
• To provide direction for any further
research needed.
• To shed light on the nature of a situation
• To identify any specific objectives or data
needs for additional research.
• Most useful when a decision maker needs
to better understand a situation
to identify decision alternatives.
Exploratory research is often conducted because a problem has not been clearly defined as yet, or its real
scope is as yet unclear. It allows the researcher to familiarize him/herself with the problem or concept to be
studied, and perhaps generate hypotheses to be tested. It is the initial research, before more conclusive
research is undertaken.
As the name implies, exploratory research is the initial exploration done to get an idea and insights
into the problem. Research is a relatively expensive process; exploratory research ensures that this
process is not initiated without a thorough understanding of the problem. This study is qualitative
(understanding the concept) rather than quantitative (providing precise measurement). Also, this
type of research does not give conclusive evidence and subsequent research needs to be done.
Further, the following purposes justify the use of exploratory research:
Exploratory Research - Research conducted to clarify and define nature of the problem
Experience
Surveys
individuals with
knowledge
about a
particular
research
problem are
surveyed
Secondary
Data Analysis
data collected
for some other
purpose is
reviewed to
solve early
stage
problems of
research
Case Studies
thoroughly
investigating
few
situations
similar to the
research
problem at
hand
Pilot Studies
small scale
research
project using
sampling but
no rigorous
standards are
applied
Focus Group
A group
discussion
conducted
with the
participation
of and 7 - 12
people to
capture their
experiences
and views
Literature
Survey
search of all
types of
published
literature in
order to
identify a
breadth of
good quality
references
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Phenomenological research
Phenomenological research an inductive, descriptive research approach developed from phenomenological
philosophy; its aim is to describe an experience as it is actually lived by the person(also refer to page 22)
Phenomenology is the study of structures of consciousness as experienced from the first-person point of view.
Literally, phenomenology is the study of “phenomena”: appearances of things, or things as they appear in our
experience, or the ways we experience things, thus the meanings things have in our experience.
Phenomenology studies conscious experience as experienced from the subjective or first person point of view.
This field of philosophy is then to be distinguished from, and related to, the other main fields of philosophy:
ontology (the study of being or what is), epistemology (the study of knowledge), logic (the study of valid
reasoning), ethics (the study of right and wrong action), etc. is often restricted to the characterization of
sensory qualities of seeing, hearing, etc.: what it is like to have sensations of various kinds. However, our
experience is normally much richer in content than mere sensation.
Basically, phenomenology studies the structure of various types of experience ranging from perception,
thought, memory, imagination, emotion, desire, and volition to bodily awareness, embodied action, and social
activity, including linguistic activity.
• Phenomenology is concerned with the study of experience from the perspective of the individual,
‘bracketing’ taken-for-granted assumptions and usual ways of perceiving.
• They are based in a paradigm of personal knowledge and subjectivity, and emphasise the importance
of personal perspective and interpretation.
• As such they are powerful for understanding subjective experience, gaining insights into people’s
motivations and actions, and cutting through the clutter of taken-for-granted assumptions and
conventional wisdom.
Ex-Post Facto Research
The term ex post facto in Latin means 'after the fact.' Example an ex post facto law is a law that is passed after
the fact that criminalizes an action that was legal when it was committed like changing the age of juvenile
from 18 to 16 after they are found to commit heinous crimes.
An ex post facto research design is a method in which groups with qualities that already exist are compared on
some dependent variable. Also known as "after the fact" research, an ex post facto design is considered quasi-
experimental because the subjects are not randomly assigned - they are grouped based on a particular
characteristic or trait.
Although differing groups are analyzed and compared in regards to independent and dependent variables it is
not a true experiment because it lacks random assignment. The assignment of subjects to different groups is
based on whichever variable is of interest to the researchers.
For example, a researcher is interested in how weight influences self-esteem levels in adults. So the
participants would be separated into differing groups (underweight, normal weight, overweight) and their self-
esteem levels measured. This is an ex post facto design because a pre-existing characteristic (weight) was used
to form the groups.
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Variable
Scientists use an experiment to search for cause and effect relationships in nature. In other words, they design
an experiment so that changes to one item cause something else to vary in a predictable way.
These changing quantities are called variables. A variable is any factor, trait, or condition that can exist in
differing amounts or types. An experiment usually has three kinds of variables:
①independent, ②dependent, and ③controlled.
Independent variable:
The independent variable is the one that is changed by the scientist. To ensure a fair test, a good experiment
has only one independent variable. As the scientist changes the independent variable, he or she observes what
happens.
Dependent variable:
The scientist focuses his or her observations on the dependent variable to see how it responds to the change
made to the independent variable. The new value of the dependent variable is caused by and depends on the
value of the independent variable.
For example, if you open a faucet (the independent variable), the quantity of water flowing (dependent
variable) changes in response--you observe that the water flow increases. The number of dependent variables
in an experiment varies, but there is often more than one.
Controlled variables:
Experiments also have controlled variables. Controlled variables are quantities that a scientist wants to
remain constant, and he must observe them as carefully as the dependent variables. For example, if we want
to measure how much water flow increases when we open a faucet, it is important to make sure that the
water pressure (the controlled variable) is held constant. That's because both the water pressure and the
opening of a faucet have an impact on how much water flows. If we change both of them at the same time, we
can't be sure how much of the change in water flow is because of the faucet opening and how much because
of the water pressure. In other words, it would not be a fair test. Most experiments have more than one
controlled variable. Some people refer to controlled variables as "constant variables."
In an experiment, if you have multiple trials, you want to reduce the number of changes between each trial. If
you tell the ball throwers on the first day to toss a ping-pong ball into a little red cup, and on the second day
you tell ball throwers to hurl a bowling ball into a barrel, your results are going to be different.
Each experiment has control variables, which are variables that are kept the same in each trial. These would
be things like:
• Ball size and weight
• Number of people in each trial
• Where participants are throwing the ball and
• Instructions of what to do
In a good experiment, the scientist must be able to measure the values for each variable. Weight or mass is an
example of a variable that is very easy to measure. However, imagine trying to do an experiment where one of
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the variables is love. There is no such thing as a "love-meter." You might have a belief that someone is in love,
but you cannot really be sure, and you would probably have friends that don't agree with you. So, love is not
measurable in a scientific sense; therefore, it would be a poor variable to use in an experiment.
As a researcher, you're going to perform an experiment
Hunger and Performance: so let's say your experiment will examine four people's ability to throw a ball when
they haven't eaten for a specific period of time - 6, 12, 18 and 24 hours.
We can say that in your experiment, you are going to do something and then see what happens to other things.
But, that sentence isn't very scientific. So, we're going to learn some new words to replace the unscientific
ones, so we can provide a scientific explanation for what you're going to do in your experiment.
The starting point here is to identify what a variable is. A variable is defined as anything that has a quantity or
quality that varies. Your experiment's variables are not eating and throwing a ball.
Now, let's science up that earlier statement, ‘You are going to manipulate a variable to see what happens to
another variable.' It still isn't quite right because we're using the blandest term for variable and we didn't
differentiate between the variables. Let's take a look at some other terms that will help us make this
statement more scientific and specific.
Independent: Hrs. (not eaten)
Dependent : Ability to throw a ball
A moment ago, we discussed the two variables in our experiment - hunger and throwing a ball. But, they are
both better defined by the terms 'dependent' or 'independent' variable.
The dependent variable is the variable a researcher is interested in. The changes to the dependent variable
are what the researcher is trying to measure with all their fancy techniques. In our example, your dependent
variable is the person's ability to throw a ball. We're trying to measure the change in ball throwing as
influenced by hunger.
An independent variable is a variable believed to affect the dependent variable. This is the variable that you,
the researcher, will manipulate to see if it makes the dependent variable change. In our example of hungry
people throwing a ball, our independent variable is how long it's been since they've eaten.
To reiterate, the independent variable is the thing over which the researcher has control and is manipulating.
In this experiment, the researcher is controlling the food intake of the participant. The dependent variable is
believed to be dependent on the independent variable.
Your experiment's dependent variable is the ball throwing, which will hopefully change due to the
independent variable. So now, our scientific sentence is, 'You are going to manipulate an independent variable
to see what happens to the dependent variable.'
The simplest experimental design includes two variables and two groups of participants.
The two variables (Independent versus Dependent variables)
• The IV is the predictor variable whereas the DV is the outcome variable.
• Researchers manipulate and control the IV to study its effect on the DV.
The two groups of participants (Control versus Experimental group).
• Before beginning the experiment, the researcher (randomly) assigns his/her sample to two different
groups: the control group and the experimental (treatment group or clinical group).
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2. Purposive /Judgment Sampling
• Also called as the Purposive sampling.
• Firstly, a sample is drawn from the population, which a researcher thinks to be a representative of the
population.
• All the members do not get the chance to get selected in the sample.
In judgement sampling researcher relies on his or her own judgement when choosing members of population
to participate in the study.
Judgement sampling is a non-probability sampling method and it occurs when “elements selected for the
sample are chosen by the judgement of the researcher. Researchers often believe that they can obtain a
representative sample by using a sound judgement, which will result in saving time and money”.
Judgment sampling is used quite frequently in qualitative research where the desire is to develop hypothesis
rather than to generalize to larger populations.
Example: In previous example of interviewing 10,000 university students, if we were only interested in
achieving a sample size of say 100 students, we may simply stand at the entrance to a particular campus most
convenient to us, where it would be easy to invite the many students that pass by to take part in the research.
Alternatively, judgement sampling method may prove to be effective when only limited numbers of people
can serve as primary data sources due to the nature of research design and aims and objectives.
For example, for a research analyzing effects of personal tragedy such as family bereavement on performance
of senior level managers the researcher may use his/her own judgement in order to choose senior level
managers who could particulate in in-depth interviews.
This sampling method offers the following advantages:
• Less time and low cost consuming compared to many other sampling methods because only suitable
candidates are targeted
• Results of purposive sampling are usually more representative of target population compared to other
sampling methods
• Purposive sampling can be the only way to recruit the members of rare or much sought after groups
Purposive sampling may be associated with the following disadvantages:
• Limited representation of wider population
• low level of reliability and high levels of personal bias
Types of Judgmental sampling:
a) Typical case: Explains cases that are average and normal.
b) Extreme or deviant case: Deriving samples from cases that are perceived as unusual or rare such as
exploring the reasons for corporate failure by interviewing executives that have been fired by shareholders.
c) Convenience: The choice of purposive sampling only due to its convenience in terms of saving time,
money and efforts. This specific case is naturally associated with lower research validity and credibility.
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Frequency Distribution:
In statistics, a frequency distribution is a table that displays the frequency of various outcomes in a sample.
Each entry in the table contains the frequency or count of the occurrences of values within a particular group
or interval, and in this way, the table summarizes the distribution of values in the sample.
An example of a univariate (i.e. single variable) frequency table, the frequency of each response to a survey
question is depicted.
Rank Degree of agreement Number
1 Strongly agree 20
2 Agree somewhat 30
3 Not sure 20
4 Disagree somewhat 15
5 Strongly disagree 15
A different tabulation scheme aggregates values into bins such that each bin encompasses a range of values.
For example, the heights of the students in a class could be organized into the following frequency table.
Height range Number of students Cumulative number
less than 5.0 feet 25 25
5.0–5.5 feet 35 60
5.5–6.0 feet 20 80
6.0–6.5 feet 20 100
A frequency distribution shows us a summarized grouping of data divided into mutually exclusive classes and
the number of occurrences in a class. It is a way of showing unorganized data e.g. to show results of an
election, income of people for a certain region, sales of a product within a certain period, student loan
amounts of graduates, etc. Some of the graphs that can be used with frequency distributions are histograms,
line charts, bar charts and pie charts. Frequency distributions are used for both qualitative and quantitative
data.
One-Way Tables in Statistics
A one-way table is the tabular equivalent of a bar chart. Like a bar chart, a one-way table displays categorical
data in the form of frequency counts and/or relative frequencies.
A one-way table is distinguished from a two-way table (described in the next lesson); because the data entries
in a one-way table refer to one variable, whereas the data entries in a two-way table refer to two variables.
When a one-way table shows frequency counts for a particular category of a categorical variable, it is called a
frequency table.
Below, the bar chart and the frequency table display the same data. Both show frequency counts, representing
travel choices of 10 travel agency clients.
Choice USA Europe Asia
Frequency 5 3 2
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Margin of Error (Confidence Interval)
No sample will be perfect, so you need to decide how much error to allow. The confidence interval determines
how much higher or lower than the population mean you are willing to let your sample mean fall. The margin
of error expresses the maximum expected difference between the true population mean and a sample
estimate of that mean.
For example, a pollster might report that 50% of voters will choose a BJP candidate. To indicate the quality of
the survey result, the pollster might add that the margin of error is +5%, with a confidence level of 90%. This
means that if the survey were repeated many times with different samples, the true percentage of BJP voters
would fall within the margin of error 90% of the time.
The Critical Value
There should then be limits set on the critical value, beyond which you can assume that the experiment proves
that the null hypothesis is false and therefore using statistical hypothesis testing, the experiment shows there
is enough evidence to reject the null hypothesis. This is generally set at 5% or 1% chance probability.
Significance level
The significance level, also denoted as alpha or α, is the probability of rejecting the null hypothesis when it is
true. For example, a significance level of 0.05 indicates a 5% risk of concluding that a difference exists when
there is no actual difference.
We'll use these tools to test the following hypotheses(as in the below graph)
• Null hypothesis: The population mean equals the hypothesized mean (260).
• Alternative hypothesis: The population mean differs from the hypothesized mean (260).
These types of definitions can be hard to understand because of their technical nature. A picture makes the
concepts much easier to comprehend!
The significance level determines how far out from the null hypothesis value we'll draw that line on the graph.
To graph a significance level of 0.05, we need to shade the 5% of the distribution that is furthest away from
the null hypothesis.
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Factor analysis
The main applications of factor analytic techniques are: (1) to reduce the number of variables and (2) to
detect structure in the relationships between variables, that is to classify variables. Therefore, factor analysis is
applied as a data reduction or structure detection method (the term factor analysis was first introduced by
Thurstone, 1931).
Suppose we want to measure people's satisfaction with their lives. We design a satisfaction questionnaire with
various items; among other things we ask our subjects how satisfied they are with their hobbies (item 1) and
how intensely they are pursuing a hobby (item 2). Most likely, the responses to the two items are highly
correlated with each other.
Combining Two Variables into a Single Factor
You can summarize the correlation between two variables in a scatterplot. A regression line can then be fitted
that represents the "best" summary of the linear relationship between the variables. If we could define a
variable that would approximate the regression line in such a plot, then that variable would capture most of
the "essence" of the two items. Subjects' single scores on that new factor, represented by the regression line,
could then be used in future data analyses to represent that essence of the two items. In a sense we have
reduced the two variables to one factor. Note that the new factor is actually a linear combination of the two
variables.
If we extend the two-variable example to multiple variables, then the computations become more involved,
but the basic principle of expressing two or more variables by a single factor remains the same.
Sign test
The sign test is a statistical method to test for consistent differences between pairs of observations, such as
the weight of subjects before and after treatment. Given pairs of observations (such as weight pre- and post-
treatment) for each subject, the sign test determines if one member of the pair (such as pre-treatment) tends
to be greater than (or less than) the other member of the pair (post-treatment).
The paired observations may be designated x and y.
For comparisons of paired observations (x,y), the sign test is most useful if comparisons can only be expressed
as x > y, x = y, or x < y. If, instead, the observations can be expressed as numeric quantities (x = 7, y = 18), or as
ranks (rank of x = 1st, rank of y = 8th), then the paired t-test or the Wilcoxon signed-rank test. will usually have
greater power than the sign test to detect consistent differences.
If X and Y are quantitative variables, the sign test can be used to test the hypothesis that the difference
between the median of X and the median of Y is zero, assuming continuous distributions of the two random
variables X and Y, in the situation when we can draw paired samples from X and Y.
The sign test can also test if the median of a collection of numbers is significantly greater than or less than a
specified value. For example, given a list of student grades in a class, the sign test can determine if the median
grade is significantly different from, say, 75 out of 100.
The sign test is a non-parametric test which makes very few assumptions about the nature of the distributions
under test - this means that it has very general applicability but may lack the statistical power of the
alternative tests.
Run Test
Run test (Wald Wolfowitz test) is a non-parametric test, that examines a sequence of numbers or characters in
a string (one after another) and determines their randomness, thus it can prove or disprove a null
hypothesis. These are observations from a random variable say X or can even combine results from two
variables X and Y
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Paper, Article
Paper
Research paper may refer to:
• Academic paper (also called scholarly paper), which is published in academic journals and contains
original research results or reviews existing results
• Term paper, written by college students
• Thesis or dissertation, a document submitted in support of a candidature for a degree or professional
qualification, presenting the author's research and findings
Academic Paper / Scholarly paper: In academic publishing, a paper is an academic work that is usually
published in an academic journal. It contains original research results or reviews existing results. Such a paper,
also called an article, will only be considered valid if it undergoes a process of peer review by one or more
referees (who are academics in the same field) who check that the content of the paper is suitable for
publication in the journal. A paper may undergo a series of reviews, editions and resubmissions before finally
being accepted or rejected for publication. This process typically takes several months. Next there is often a
delay of many months (or in some subjects, over a year) before an accepted manuscript appears.
Some journals, particularly newer ones, are now published in electronic form only. Paper journals are now
generally made available in electronic form as well, both to individual subscribers, and to libraries.
Term paper: A term paper' is a research paper written by students over an academic term. Term papers are
generally intended to describe an event, a concept, or argue a point. A term paper is a written original work
discussing a topic in detail, usually several typed pages in length and is often due at the end of a semester ∕
session. There is much overlap between the terms "research paper" and "term paper". The phrase "term
paper" was originally used to describe a paper (usually a research based paper) that was due at the end of the
"term" - either a semester or session, depending on which unit of measure a school used. Common usage has
"term paper" and "research paper" as interchangeable, but this is not completely accurate. Not all term papers
involve academic research, and not all research papers are term papers.
In the present day an entire industry has sprung up to provide plagiarized, pre-written, or custom written term
papers to students. Use of such papers is frowned upon by educators and administrators, and submission of
these works is considered plagiarism, and grounds for disciplinary action on the basis of academic dishonesty.
Thesis: A dissertation or thesis is a document submitted in support of candidature for an academic degree or
professional qualification presenting the author's research and findings. In some countries/ universities, the
word "thesis" or a cognate is used as part of a bachelor's or master's course, while "dissertation" is normally
applied to a doctorate, while in others, the reverse is true.
The word dissertation can at times be used to describe a treatise without relation to obtaining an academic
degree. The term thesis is also used to refer to the general claim of an essay or similar work.
Article
A research article reports the results of original research, assesses its contribution to the body of knowledge in
a given area, and is published in a peer-reviewed scholarly journal. A given academic field will likely have
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dozens of peer-reviewed journals. For university professors, publishing their research plays a key role in
determining whether they are granted tenure. Once, research articles had only a limited audience consisting
Quality of a research journal
Journals that are included on the ISI (Institute of Scientific Information) databases have been through a
rigorous selection process including peer review. ISI produces statistical analysis of journals, most widely used
is the journal impact factor although the immediacy index and citing half-life are also useful indicators. The
literature suggests the impact factor is just one of a suite of measures that should be used in conjunction with
"measures of esteem, performance, visibility and testimony of peers expert in relation to the activity that is
being analysed".
Impact factor
Impact factor, an index based on the frequency with which a journal's articles are cited in scientific
publications, is a putative marker of journal quality.
The impact factor of a journal reflects the frequency with which the journal's articles are cited in the scientific
literature. It is derived by dividing the number of citations in year 3 to any items published in the journal in
years 1 and 2 by the number of substantive articles published in that journal in years 1 and 2 . For instance, the
year 2002 impact factor for Journal X is calculated by dividing the total number of citations during the year
2002 to items appearing in Journal X during 2000 and 2001 by the number of articles published in Journal X in
2000 and 2001.
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A = Total citations in 2002 to items published in Journal X B = 2002 citations to items published in Journal X in
2000-01 (subset of A) C = Number of substantive articles published in Journal X in 2000-01
Impact factor = B/C
Example:
Assume that in 2002. There were 3,200 citations to items published in Journal X. Of these, 550 were citations to
items published in Journal X in 2000 and 2001.
During those two years. Journal X published 72 articles.
2002 Journal X impact factor = 550/72 = 7.64
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Impact factor is used by librarians in selecting journals for library collections, and, in some countries, it is used
to evaluate individual scientists and institutions for the purposes of academic promotion and funding
allocation.
The use of impact factor as an index of journal quality relies on the theory that citation frequency accurately
measures a journal's importance to its end users. This theory is plausible for journals whose audiences are
primarily researchers, most of whom write manuscripts for publication. By citing articles from a given journal
in their own manuscripts, researchers are in essence casting votes for that journal. Impact factor serves as a
tally of those votes.
The immediacy index
is calculated by dividing the number of citations to articles published in a given year by the number of articles
published in that year. It is useful in comparing how quickly journals are cited.
The citing half-life
is the number of publication years from the current year that account for 50% of
the current citations published by a journal in its article references. This helps evaluate the age of
the majority of articles referenced by a journal, while dramatic changes in the citing half-lifes over
time may indicate a change in a journal's format.
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