EMPIRICAL RESEARCH METHOD Part2.pptx
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The document outlines the steps in conducting empirical research which includes selecting a research problem, reviewing existing literature, formulating a hypothesis, choosing a research design, collecting data, analyzing results, and stating conclusions. Empirical research involves testing hypotheses through experimentation, observation or experience. It has advantages such as being used for authentication and understanding dynamic changes, but also disadvantages like being time consuming and expensive.
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introduction Research methodology
Research methodology provides guidance on conducting research systematically and scientifically. It explains both qualitative and quantitative research methods and the steps of the research process, including defining the problem, reviewing literature, developing hypotheses, collecting and analyzing data, and reporting findings. Key aspects of research methodology include formulating testable hypotheses, designing studies (e.g. experiments) to test hypotheses, and using statistical analysis to accept or reject null hypotheses.
Analysis of data in research
Analysis of data is a process of inspecting, cleaning, transforming, and modeling data with the goal of discovering useful information, suggesting conclusions, and supporting decision-making.
Lesson 2 selection of research topic
This is lesson 2 of the course on Research Methodology conducted at the Faculty of Social Sciences and Humanities of the Rajarata University of Sri Lanka
research method vs. methodology
Research methods refer to the tools and techniques used to undertake a research study, such as surveys, interviews, experiments, etc. Research methodology is the systematic approach and justification for using specific research methods. It ensures accurate and valid conclusions by clarifying the logic and reasons for choosing certain methods over others. Research methods are employed later in the research process to find solutions, while research methodology guides the initial process to determine the most appropriate methods.
Concept of research design
This document discusses research design. It defines research design as the planned sequence of the entire research process, including the framework of methods chosen. A good research design includes accurate purpose and methodology statements, appropriate settings and techniques for data collection and analysis, and consideration of timeline and measurements. Key aspects of research design include type of data needed, participants, variables or research questions, and data analysis methods. Choosing a research design requires considering priorities, practicalities, and the type of primary or secondary, qualitative or quantitative data required, as well as how that data will be collected and analyzed.
Hypothesis Testing
Hypothesis Testing is important part of research, based on hypothesis testing we can check the truth of presumes hypothesis (Research Statement or Research Methodology )
Inferential Statistics
This document provides an overview of various statistical analysis techniques used in inferential statistics, including t-tests, ANOVA, ANCOVA, chi-square, regression analysis, and interpreting null hypotheses. It defines key terms like alpha levels, effect sizes, and interpreting graphs. The overall purpose is to explain common statistical methods for analyzing data and determining the probability that results occurred by chance or were statistically significant.
Research Design and Types of Research Design Arun Joseph MPhil ppt
Research Design and Types of Research Design Arun Joseph MPhil pptArun Joseph (Librarian), MLISc, UGC NET
This document discusses research design and different types of research designs. It defines research design as the conceptual structure and plan for conducting research to answer research questions. The main types of research designs covered are exploratory, descriptive, diagnostic, and experimental. Exploratory design is used when little is known about a topic to discover variables and relationships. Descriptive design aims to describe phenomena by observing behaviors. Diagnostic design involves problem identification and finding causes. Experimental design tests hypotheses by manipulating variables and measuring outcomes. The document provides details on each design type, including their purposes and methodologies.Recommended
introduction Research methodology
Research methodology provides guidance on conducting research systematically and scientifically. It explains both qualitative and quantitative research methods and the steps of the research process, including defining the problem, reviewing literature, developing hypotheses, collecting and analyzing data, and reporting findings. Key aspects of research methodology include formulating testable hypotheses, designing studies (e.g. experiments) to test hypotheses, and using statistical analysis to accept or reject null hypotheses.
Analysis of data in research
Analysis of data is a process of inspecting, cleaning, transforming, and modeling data with the goal of discovering useful information, suggesting conclusions, and supporting decision-making.
Lesson 2 selection of research topic
This is lesson 2 of the course on Research Methodology conducted at the Faculty of Social Sciences and Humanities of the Rajarata University of Sri Lanka
research method vs. methodology
Research methods refer to the tools and techniques used to undertake a research study, such as surveys, interviews, experiments, etc. Research methodology is the systematic approach and justification for using specific research methods. It ensures accurate and valid conclusions by clarifying the logic and reasons for choosing certain methods over others. Research methods are employed later in the research process to find solutions, while research methodology guides the initial process to determine the most appropriate methods.
Concept of research design
This document discusses research design. It defines research design as the planned sequence of the entire research process, including the framework of methods chosen. A good research design includes accurate purpose and methodology statements, appropriate settings and techniques for data collection and analysis, and consideration of timeline and measurements. Key aspects of research design include type of data needed, participants, variables or research questions, and data analysis methods. Choosing a research design requires considering priorities, practicalities, and the type of primary or secondary, qualitative or quantitative data required, as well as how that data will be collected and analyzed.
Hypothesis Testing
Hypothesis Testing is important part of research, based on hypothesis testing we can check the truth of presumes hypothesis (Research Statement or Research Methodology )
Inferential Statistics
This document provides an overview of various statistical analysis techniques used in inferential statistics, including t-tests, ANOVA, ANCOVA, chi-square, regression analysis, and interpreting null hypotheses. It defines key terms like alpha levels, effect sizes, and interpreting graphs. The overall purpose is to explain common statistical methods for analyzing data and determining the probability that results occurred by chance or were statistically significant.
Research Design and Types of Research Design Arun Joseph MPhil ppt
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This document discusses research design and different types of research designs. It defines research design as the conceptual structure and plan for conducting research to answer research questions. The main types of research designs covered are exploratory, descriptive, diagnostic, and experimental. Exploratory design is used when little is known about a topic to discover variables and relationships. Descriptive design aims to describe phenomena by observing behaviors. Diagnostic design involves problem identification and finding causes. Experimental design tests hypotheses by manipulating variables and measuring outcomes. The document provides details on each design type, including their purposes and methodologies.Data collection
Data collection in research involves systematically gathering factual information to test hypotheses or answer research questions. There are two main types of data: primary data collected directly by researchers through methods like surveys and interviews, and secondary data previously collected by others. The document outlines purposes of data collection like research design and sampling, as well as methods for primary data collection including questionnaires, interviews, focus groups, observation, and case studies. Both primary and secondary data have advantages and disadvantages for research.
Data Collection
This document discusses various methods for collecting primary and secondary data for research. It explains that primary data is collected fresh for a study, while secondary data comes from existing sources like books, papers, and reports. Some primary data collection methods covered include surveys, experiments, interviews, questionnaires, schedules, case studies, and observation. Factors to consider when choosing a method include the research objectives, budget, timeframe, and the researcher's knowledge. Collecting quality data is essential for answering the research problem.
Research methodology
The document discusses various aspects of research methodology including types of research, the research process, and criteria for good research. It describes the main types of research as applied, basic, correlational, descriptive, ethnographic, experimental, exploratory, and historical. The research process involves defining the problem, reviewing literature, designing the methodology, collecting and analyzing data, and interpreting and reporting findings. Criteria for good research include having a clear definition, explainable design, sufficient data, and validity and reliability checks.
Data Collection & Analysis
The document discusses considerations for data collection plans including objectives, scope, sources, methods, units of measurement, and accuracy levels. It defines primary and secondary data, as well as qualitative and quantitative data. Sources of primary data include interviews, questionnaires, and observation, while published/unpublished sources and databases are sources of secondary data. Secondary data has advantages like being easy to generalize from, economical, and quick, but reliability can be difficult to determine and inherent limitations may exist. Questionnaires should be clearly written following principles like being precise, unbiased, and pilot tested.
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This document provides information on data collection methods and statistical analysis. It discusses various types of data collection including observation, interviews, questionnaires, surveys, and case studies. It also covers primary and secondary sources of data. The document outlines steps for processing and analyzing data such as editing, coding, tabulation, and classification. It describes various statistical tools for analysis including measures of central tendency, dispersion, t-tests, and chi-square tests. Guidelines are provided for writing reports to communicate the results of a research study.
Research Methodology
The presentation would help post graduate students, research scholars, academicians and NGOs involved in research to understand research methodology in a simple manner.
To have a clear understanding of research methodology you can view the upcoming presentations which will be uploaded soon.
Test of hypothesis
The document discusses hypothesis testing in research. It defines a hypothesis as a proposition that can be tested scientifically. The key points are:
- A hypothesis aims to explain a phenomenon and can be tested objectively. Common hypotheses compare two groups or variables.
- Statistical hypothesis testing involves a null hypothesis (H0) and alternative hypothesis (Ha). H0 is the initial assumption being tested, while Ha is what would be accepted if H0 is rejected.
- Type I errors incorrectly reject a true null hypothesis. Type II errors fail to reject a false null hypothesis. Hypothesis tests aim to control the probability of type I errors.
- The significance level is the probability of a type I error,
Quantitative Data - A Basic Introduction
Part of a course I run introducing quantitative methods. One of the slideshows on my site www.kevinmorrell.org.uk please reference the site if you use any of it - hope it is useful.
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The document discusses the key hallmarks of scientific research including:
1) Purposiveness - Research is undertaken with a clear purpose and objective to identify problems or areas of inquiry.
2) Rigor - A theoretical base and sound methodology add rigor and exactitude to research.
3) Testability - Research designs formulate hypotheses, collect data, and analyze it to achieve study objectives and make findings testable and replicable.
4) Generalizability - The results of fundamental research should be applicable and acceptable to a wide range of organizations.
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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.
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This document provides an overview of various quantitative data analysis techniques including parametric and non-parametric statistics, descriptive statistics, contingency analysis, t-tests, ANOVA, correlation, and regression. It discusses assumptions and processes for each technique and how to interpret results. Computer software like SPSS and SAS can be used to analyze large, complex datasets.
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9.testing of hypothesis
1. The document discusses various statistical tests used for testing hypotheses, including t-tests, ANOVA, non-parametric tests, and tests of correlation and relationships between variables.
2. Key concepts covered include the difference between null and alternative hypotheses, types of errors, p-values, assumptions of different tests, and choosing appropriate tests based on the scale and distribution of the data.
3. Examples are given of common tests like paired t-test, Wilcoxon test, repeated measures ANOVA, independent t-test, and tests for comparing multiple groups like ANOVA and Kruskal-Wallis test. Tests of relationships like correlation, regression, chi-square, and Fisher's exact test are also summarized
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The document discusses identifying and selecting a good research problem. It notes that identifying a research problem is the first and most challenging step of the research process. A good research problem should be significant, original, feasible, solvable, current, and interesting. The document provides examples and criteria for selecting a research problem, as well as common sources that researchers draw from in identifying problems, such as personal experiences, literature reviews, previous research, and social issues.
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2. It provides examples of when to use a z-test or t-test, and walks through the steps of conducting a one-sample t-test including stating hypotheses, determining critical values, computing test statistics, and making conclusions.
3. An example problem demonstrates these steps, testing if a therapy reduces test anxiety below a population mean of 20, finding the sample mean is significantly lower.
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Research is a process through which new knowledge is discovered. Conducting research has to follow certain steps and these may vary with the type and goals of research. But the variation in the process would be minor according to the study involves quantitative or a qualitative approach and data.
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This document discusses various methods for collecting primary and secondary data for research. It explains that primary data is collected fresh for a study, while secondary data comes from existing sources like books, papers, and reports. Some primary data collection methods covered include surveys, experiments, interviews, questionnaires, schedules, case studies, and observation. Factors to consider when choosing a method include the research objectives, budget, timeframe, and the researcher's knowledge. Collecting quality data is essential for answering the research problem.
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The document discusses various aspects of research methodology including types of research, the research process, and criteria for good research. It describes the main types of research as applied, basic, correlational, descriptive, ethnographic, experimental, exploratory, and historical. The research process involves defining the problem, reviewing literature, designing the methodology, collecting and analyzing data, and interpreting and reporting findings. Criteria for good research include having a clear definition, explainable design, sufficient data, and validity and reliability checks.
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The document discusses considerations for data collection plans including objectives, scope, sources, methods, units of measurement, and accuracy levels. It defines primary and secondary data, as well as qualitative and quantitative data. Sources of primary data include interviews, questionnaires, and observation, while published/unpublished sources and databases are sources of secondary data. Secondary data has advantages like being easy to generalize from, economical, and quick, but reliability can be difficult to determine and inherent limitations may exist. Questionnaires should be clearly written following principles like being precise, unbiased, and pilot tested.
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The presentation would help post graduate students, research scholars, academicians and NGOs involved in research to understand research methodology in a simple manner.
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- A hypothesis aims to explain a phenomenon and can be tested objectively. Common hypotheses compare two groups or variables.
- Statistical hypothesis testing involves a null hypothesis (H0) and alternative hypothesis (Ha). H0 is the initial assumption being tested, while Ha is what would be accepted if H0 is rejected.
- Type I errors incorrectly reject a true null hypothesis. Type II errors fail to reject a false null hypothesis. Hypothesis tests aim to control the probability of type I errors.
- The significance level is the probability of a type I error,
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1) Purposiveness - Research is undertaken with a clear purpose and objective to identify problems or areas of inquiry.
2) Rigor - A theoretical base and sound methodology add rigor and exactitude to research.
3) Testability - Research designs formulate hypotheses, collect data, and analyze it to achieve study objectives and make findings testable and replicable.
4) Generalizability - The results of fundamental research should be applicable and acceptable to a wide range of organizations.
Topic Selection
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2. Key concepts covered include the difference between null and alternative hypotheses, types of errors, p-values, assumptions of different tests, and choosing appropriate tests based on the scale and distribution of the data.
3. Examples are given of common tests like paired t-test, Wilcoxon test, repeated measures ANOVA, independent t-test, and tests for comparing multiple groups like ANOVA and Kruskal-Wallis test. Tests of relationships like correlation, regression, chi-square, and Fisher's exact test are also summarized
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2. It provides examples of when to use a z-test or t-test, and walks through the steps of conducting a one-sample t-test including stating hypotheses, determining critical values, computing test statistics, and making conclusions.
3. An example problem demonstrates these steps, testing if a therapy reduces test anxiety below a population mean of 20, finding the sample mean is significantly lower.
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This ppt contains Probability Sampling Method- Concept - Types which also covers Types of Sampling
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- 2. Empirical Research Empirical research is the process of testing a hypothesis using experimentation, direct or indirect observation and experience.
- 3. Steps in Conducting Empirical Research The chart below shows the steps researchers commonly follow investigating a problem.
- 4. SELECTING A RESEARCHABLE PROBLEM Finding a problem that merits study and that can be investigated by the methods of science. REVIEWING THE LITERATURE Surveying the existing theory and research on the subject. FORMULATING A HYPOTHESIS Arriving at statement that specifies the relationship between the variables and developing an operational definition that states the variables in a form that permits their measurement 1 2 3
- 5. CHOOSING A RESEARCH DESIGN Determining whether to test the hypothesis by designing an experiment, conducting interviews, observing the way people behave in particular situations, examining existing records and historical evidence, or combining these procedures. COLLECTING THE DATA Gathering the data and recording it in accordance with the specifications of the research design. 4 5
- 6. ANALYZING THE RESULTS Searching for meaningful links between the facts that emerged in the course of the research. STATING CONCLUSIONS Indicating the outcome of the study, extracting the broader meaning of the work for other knowledge and research, and suggesting future directions for future research. 6 7
- 7. Test the hypothesis entails returning to empirical methods to put the hypothesis to the test. It is the process of reaching a conclusion by considering whether a collection of broader premises supports a specific claim. It relies on logic and rationality to come to specific conclusions given general premises. It involves collecting and organizing empirical data. The research outlines the empirical data, the research findings and the supporting arguments plus any challenges encountered during the research process.
- 8. • Used for authentication • Used for understanding dynamic changes • Provides a level of control • Increases internal validity Advantages of Empirical Research
- 9. • Time consuming • Expensive • Difficult to acquire consent/permission • Collection of data can be a problem Disadvantages of Empirical Research
- 10. • It is used to validate various hypotheses or refute them in the face of evidence. • It increases human knowledge and continue doing it to keep advancing in various fields. Importance of Empirical Research