Research Methodology
- Description
- Curriculum
- FAQ
- Reviews
Learn about key concepts of Research Methodology such as Research Problem, Research Design, Sampling Techniques, Research Proposal, Data Collection, Data Analysis, and Research Report (Dissertation/Thesis). This course aims to explain the concepts within shortest time possible whilst keeping it real SIMPLE.
This course designed to be practical. The theoretical knowledge that constitutes research methodology is therefore organised around the operational steps that form this research process for both Quantitative and Qualitative research.
I have taken a very bold step in breaking down, where possible, the wall between qualitative and quantitative research by describing both methodologies parallel to one another within a common framework.
This course will primarily benefit 3 groups.
Students: Who are newcomers to academic research and have therefore assumed students of NOTÂ having any prior knowledge.
Professionals: Gain significant knowledge on concepts of market research or journal writing.
Academic Supervisor: Use this course to teach students about key research concepts.
This course will not teach how to do statistical calculations. Statistic is not a core element of a research. You can conduct a perfect research work without conducting any statistical calculations. Moreover, the type of statistical calculations used for research varies markedly – from person to person, from discipline to discipline.
Stay tuned, enjoy the course and feel free to ask questions if you have any. If you would like subtitles in different languages, let me know. Good luck
Captions: English. Subtitles: Spanish, Dutch, Portuguese, Italian, German, French, and Turkish.
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Section IntroductionThis lecture explains the content of the course - 1. Literature Review, 2. Research Problem, 3. Variables, 4. Hypotheses, 5. Operational Definition
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Literature Review
Explanation of Literature Review, Benefits of Literature Review, Steps in Literature Review and how to document Literature Review.Â
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Research Problem
What is Research Problem, Importance of Research Problem, Sourcing Research Problem, Steps in Formulating Research Problem, The Good and Bad Research Problem, Research Objectives, Research Problem - Qualitative vs. Quantitative
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Variables
What is a Variable, Types of Variable, Measurement Scale.
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Hypothesis
What is a Hypothesis, Constructing a Hypotheses, Types of Hypotheses
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Operational Definition
Operational Definition of Research
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Section Introduction
This lecture explains the content of the course - 1. Research Design, 2. Design in Qualitative Study, 3. Design in Quantitative Study, 4. Ideal Research Design
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Research Design
What is Research Design
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Design Qualitative Research Study
Research Designs in Qualitative Study
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Design Quantitative Research Study
Research Design in Quantitative Study
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Ideal Research Design
Ideal Research Design
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Section Introduction
This lecture explains the content of the course - 1. Basics of Sampling, 2. Sampling Techniques
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Basics of Sampling
What is Sampling?, Sampling Terminology, Sampling Consideration
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Sampling in Quantitative Research
Sampling Types in Quantitative Research, Random/Probability Sampling, Non-Random/Non-Probability Sampling, Mixed Sampling, Sample Size Calculation, Sampling Criteria (Quantitative vs. Qualitative)
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Section Introduction
This lecture explains the content of the course - 1. Data Collection Methods, 2. Measurement Methods
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Data Collection Methods
Types of Data Collection, Primary Data Collection (Observation, Interview, Questionnaire, Design Questionnaire), Secondary Data Collection, Test Research Instrument, Data Collection Methods in Qualitative and Quantitative
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Measurement Scale
Attitudinal Scale, Likert Scale, Likert Scale Construction
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Section Intro
This lecture explains the content of the course - 1. Ethics in Data Collection, 2. Data Analysis
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Ethics
Ethics by Definition, Ethics in Data Collection.
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Data Analysis
Steps in Data Analysis, Quantitative Analysis Techniques (Univariate, Bi-variate, Multi-variate), Measurement of Latent Variable, Cronbach’s Alpha (Reliability), Qualitative Analysis Techniques, Importance of Statistics in Data Analysis
