Interpretation of research results comendador, g.
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Numbers do not speak for themselves. Interpretation is giving meaning to the data that has been collected, analyze and presented after a study.
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This document discusses data interpretation and provides details on what interpretation is, its importance, techniques for interpretation, and precautions that should be taken. Interpretation refers to drawing inferences from collected facts after analytical study and finding broader meanings of research results. It helps explain factors observed in a study and provides guidance for future research. Proper interpretation establishes connections between studies and explanatory concepts, and is necessary to understand abstract principles and the real significance of findings.
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Research meaning, Definition, Purpose, Objectives and Process.
This document defines research and outlines the research methodology process. It states that research involves defining problems, formulating hypotheses, collecting and analyzing data, making deductions, reaching conclusions, and testing conclusions. Research is described as a systematic, formal, and rigorous process used to discover facts, relationships, and solutions to problems. The purpose of research is to gain solutions to problems through organized investigation with clearly defined objectives in order to obtain the right solution.
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Degrees of freedom represent the number of variables that can vary freely in a statistical calculation. They are used to ensure the validity of tests like the chi square test, t-tests, and F-tests by accounting for the number of observations. Degrees of freedom are calculated by subtracting constraints, like the number of groups in an experiment, from the total number of observations. Common formulas are Df=N-1 for a single sample test, and Df=n1+n2-2 for a two sample test, where N is the sample size and n1 and n2 are the sample sizes of two groups.
Research design
The document discusses various aspects of research design including:
1. Research design involves decisions about what, where, when, how much, and by what means to study a research problem.
2. Key parts of research design include sampling design, observational design, statistical design, and operational design.
3. Experimental designs aim to establish cause-and-effect relationships through control and manipulation of variables while quasi-experimental and non-experimental designs do not involve manipulation.
Formulating research objectives
This document discusses research objectives, including their meaning, characteristics, need, and types. It states that a research objective provides direction to investigate variables and is the result sought by the researcher. Objectives should be SMART (specific, measurable, attainable, realistic, and time-bound). Formulating objectives helps researchers focus, avoid issues, organize their work, and define directions. There are two types of objectives: general objectives which are broad goals, and specific objectives which are narrower and break general objectives into logically connected parts. The document provides examples to illustrate general and specific objectives for research statements.
Interpretation
The document discusses interpretation in research, which involves drawing meaningful conclusions from analyzed data. Interpretation reveals the significance of research findings and demands fair judgments. Both the analysis of data and its interpretation are interdependent processes. When interpreting data, researchers should consider factors affecting the problem, consult experts, and provide reasonable explanations while avoiding errors like making false generalizations or using improper statistical methods and measures. The goal of interpretation is to understand what was learned and help discover new relationships and predictions.
Testing of hypothesis
Hypothesis testing involves making an assumption about an unknown population parameter, called the null hypothesis (H0). A hypothesis is tested by collecting a sample from the population and comparing sample statistics to the hypothesized parameter value. If the sample value differs significantly from the hypothesized value based on a predetermined significance level, then the null hypothesis is rejected. There are two types of errors that can occur - type 1 errors occur when a true null hypothesis is rejected, and type 2 errors occur when a false null hypothesis is not rejected. Hypothesis tests can be one-tailed, testing if the sample value is greater than or less than the hypothesized value, or two-tailed, testing if the sample value is significantly different from the hypothesized value.
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Degrees of freedom represent the number of variables that can vary freely in a statistical calculation. They are used to ensure the validity of tests like the chi square test, t-tests, and F-tests by accounting for the number of observations. Degrees of freedom are calculated by subtracting constraints, like the number of groups in an experiment, from the total number of observations. Common formulas are Df=N-1 for a single sample test, and Df=n1+n2-2 for a two sample test, where N is the sample size and n1 and n2 are the sample sizes of two groups.
Research design
The document discusses various aspects of research design including:
1. Research design involves decisions about what, where, when, how much, and by what means to study a research problem.
2. Key parts of research design include sampling design, observational design, statistical design, and operational design.
3. Experimental designs aim to establish cause-and-effect relationships through control and manipulation of variables while quasi-experimental and non-experimental designs do not involve manipulation.
Formulating research objectives
This document discusses research objectives, including their meaning, characteristics, need, and types. It states that a research objective provides direction to investigate variables and is the result sought by the researcher. Objectives should be SMART (specific, measurable, attainable, realistic, and time-bound). Formulating objectives helps researchers focus, avoid issues, organize their work, and define directions. There are two types of objectives: general objectives which are broad goals, and specific objectives which are narrower and break general objectives into logically connected parts. The document provides examples to illustrate general and specific objectives for research statements.
Interpretation
The document discusses interpretation in research, which involves drawing meaningful conclusions from analyzed data. Interpretation reveals the significance of research findings and demands fair judgments. Both the analysis of data and its interpretation are interdependent processes. When interpreting data, researchers should consider factors affecting the problem, consult experts, and provide reasonable explanations while avoiding errors like making false generalizations or using improper statistical methods and measures. The goal of interpretation is to understand what was learned and help discover new relationships and predictions.
Testing of hypothesis
Hypothesis testing involves making an assumption about an unknown population parameter, called the null hypothesis (H0). A hypothesis is tested by collecting a sample from the population and comparing sample statistics to the hypothesized parameter value. If the sample value differs significantly from the hypothesized value based on a predetermined significance level, then the null hypothesis is rejected. There are two types of errors that can occur - type 1 errors occur when a true null hypothesis is rejected, and type 2 errors occur when a false null hypothesis is not rejected. Hypothesis tests can be one-tailed, testing if the sample value is greater than or less than the hypothesized value, or two-tailed, testing if the sample value is significantly different from the hypothesized value.
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This document discusses selecting and defining a research problem. It explains that a research problem needs to be clearly defined and operationalized using measurable variables. The selection process involves evaluating potential problems based on criteria like the researcher's background and available resources. Problems should be novel, solve a current issue, and allow further research. The document provides guidance on refining broad topics into narrow, specific research problems suitable for different research methods like historical, descriptive or experimental studies.
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Experimental research
Experimental research is the most conclusive scientific method because the researcher directly manipulates the independent variable and studies its effects on the dependent variable. This allows the researcher to determine causation, unlike other research methods. The purpose is to establish cause-and-effect relationships between variables. Basic steps include having an experimental group that receives a treatment and a control group that does not, then comparing outcomes. Key characteristics include random assignment to control threats to internal validity. Poor designs do not include control groups or random assignment, making it impossible to determine if results are due to the treatment.
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Subscribe to Vision Academy for Video assistance
https://www.youtube.com/channel/UCjzpit_cXjdnzER_165mIiw
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Data analysis
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Experimental research
Experimental research is the most conclusive scientific method because the researcher directly manipulates the independent variable and studies its effects on the dependent variable. This allows the researcher to determine causation, unlike other research methods. The purpose is to establish cause-and-effect relationships between variables. Basic steps include having an experimental group that receives a treatment and a control group that does not, then comparing outcomes. Key characteristics include random assignment to control threats to internal validity. Poor designs do not include control groups or random assignment, making it impossible to determine if results are due to the treatment.
Karl pearson's coefficient of correlation
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Experimental designs
Viewing the presentation will provide you an idea of the different experimental research designs that could be employed in an experimental research.
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What is Research? Types of Research
This document provides an overview of research, including definitions, characteristics, and types. It defines research as a systematic process of inquiry aimed at increasing understanding through collecting and analyzing information. The document outlines the main characteristics of research as being analytical, empirical, logical, cyclical, critical, and methodical. It also describes the main types of research based on their application, objectives, and mode of inquiry. The types discussed include pure research, applied research, descriptive research, correlational research, explanatory research, and exploratory research. Both quantitative and qualitative research methods are also defined.
Qualitative-vs.-Quantitative Research.pptx
This document differentiates between qualitative and quantitative research. Qualitative research relies on non-numerical personal accounts and observations to understand how people think, while quantitative research uses measurable data and statistical analysis to test relationships. Some key differences are that qualitative research uses interviews, documents and observations to collect open-ended data, while quantitative relies on experiments, surveys and databases to collect standardized data suitable for numerical analysis. Both approaches have benefits and limitations for addressing different types of research questions.
Week 9 validity and reliability
The document discusses validity and reliability in research. It defines reliability as the consistency of scores from one administration of an instrument to another, and validity as the appropriateness of inferences made from research findings. The document outlines different types of validity evidence including content, criterion, and construct validity. It also discusses threats to internal validity such as subject characteristics, loss of subjects, and location that could influence research outcomes. Methods for achieving validity and reliability are presented, including minimizing threats in experimental research designs.
Research Design simplified
The document discusses various stages and types of research processes. It describes the typical stages as formulating a problem, determining the research design, developing data collection methods and forms, collecting and analyzing data, and preparing the research report. It also discusses exploratory, descriptive, and explanatory research goals. Exploratory research is used to discover new ideas and form hypotheses, while descriptive research aims to observe relationships and explanatory research seeks to determine causes. The document also covers research design types like experimental, quasi-experimental, and non-experimental designs as well as qualitative and quantitative methods.
Edited assignment in research
The document discusses quantitative research methods. It begins by defining quantitative data as pieces of information that can be counted, often from large random samples. Both qualitative and quantitative methods are then described as complementary approaches. Key points about quantitative research include: it aims to determine relationships between variables; designs are descriptive or experimental; it focuses on numbers, logic and objectivity rather than divergent reasoning; and characteristics include using structured instruments, representative large samples, reliability, clearly defined questions, and numerical data. The strengths are broader generalization while weaknesses include less detail and flexibility.
Q4-W5-7_PracticalResearch1.pdf
This document provides guidance for students on their practical research assignments for weeks 5-7. It discusses key terms related to data analysis such as coding, collating, and different types of matrices. It also covers qualitative data analysis and drawing conclusions. For week 6, students are asked to explain pointers for writing a conclusion section. Week 7 involves answering questions about drawing valid conclusions and ensuring they are supported by evidence from the data analysis. The document emphasizes that conclusions must be logically supported by factual findings from the research.
Business Research Metods B.Com
The document discusses various aspects of research methods and processes. It defines research as the gathering of new knowledge from primary and secondary sources through systematic investigation. It notes that research involves identifying and formulating the problem, conducting an extensive literature review, developing hypotheses, preparing the research design, collecting and analyzing data, and preparing a research report. The key steps in the research process are formulating the problem, literature survey, developing a synopsis, identifying variables, setting hypotheses, research design, sampling, data collection, analysis, testing hypotheses, and reporting. The types of research designs discussed are exploratory, descriptive, causal, and experimental.
Research design and methods
This document provides an overview of key concepts in educational research methods. It discusses the purposes of educational research as explaining educational issues and helping to understand, predict, improve, and generate new questions. It also outlines the main steps of scientific inquiry as recognizing a problem, collecting information, analyzing data, and stating implications. The document then distinguishes between basic, applied, and evaluation research. It explains quantitative and qualitative research methods and various research designs including descriptive, correlational, causal-comparative, experimental, and historical. It also discusses sampling techniques, variables and scales of measurement, types of instruments, validity and reliability, and statistical analysis methods.
You Want Me to Measure What?
Why limit ourselves to traditional quantitative metrics like visitor count, page weight, conversion, and revenue when there is so much valuable qualitative data available? We can turn qualitative data into quantitative data and use the same rigorous analysis techniques to help lead us to better designs, products, services, and experiences.
Practical Research 2: Nature and Inquiry about research
this includes the nature and inquiry about a certain topic or thesis.
Know how of question bank development
The document discusses developing effective test questions or items. It explains that questions should be carefully planned and executed to objectively measure students' abilities. The document provides guidelines for writing clear, appropriately difficult questions that reliably discriminate between high- and low-performing students. It also discusses analyzing questions based on difficulty level, discrimination index, and effectiveness of answer options. The goal is to include questions that accurately assess learning objectives.
Qrm 210 unit 1
This document discusses qualitative research methods. It defines qualitative research as seeking to understand opinions, experiences, and feelings through subjective data rather than numerical data. The document outlines several key characteristics of qualitative research, including that it takes place in natural settings, collects non-numerical data like words or illustrations, is concerned with processes, and analyzes data inductively by drawing out general ideas. It also discusses the need for qualitative research, ethics, and ways to link qualitative and quantitative research approaches.
Q3-M7-1styr-howtomakeinquiriesss_(1).pptx
The document discusses various methods for collecting quantitative and qualitative data for research purposes. It begins by defining the purpose of research as making descriptions, explanations, and predictions about phenomena. It then outlines four types of variables that are important in quantitative research: discrete, continuous, nominal, and ordinal variables. Examples are provided for each type. The main quantitative data collection methods discussed are surveys and one-on-one interviews. Surveys can be conducted using paper, online, or other means, while interviews can be done face-to-face, by telephone, or online. Both methods aim to systematically gather numerical data that can be analyzed to answer research questions. Qualitative data and secondary data collection are also briefly covered.
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Interpretation of research results comendador, g.
- 1. Prepared by: MS General Science Education Central Mindanao University Education 241 Methods of Research in Education
- 2. Objectives: 1. Interpret research data; 2. Deal with expected and unexpected results
- 3. What does it mean that 55 youth reported change in behavior, or 25% of participants rated the program a 5 and 75% rated it a 4? What does these numbers mean? Why Interpret Research Results? For example,
- 4. What is Interpretation in Research? Interpretation refers to the task of drawing inferences from the data that has been collected, analyzed, and presented after an analytical and or experimental study. It involves making “inferences pertinent to the research relations” investigated from where generalizations are drawn (Calderon & Gonzales, 1993).
- 5. Interpretation reflects the researcher’s own understanding of the research results which are guided by logic and reason, established theories and previous findings.
- 7. 2 Types of Data to Interpret • Quantitative Data • Qualitative Data
- 8. Qualitative data includes narratives, logs, experience from Focus groups, interviews, open-ended survey items, diaries and journals, notes from observations and etc.
- 9. • demographic data • answers to closed-ended survey items • attendance data • scores on standardized instruments • etc. Quantitative data are data that is numerical, counted, or compared on a scale
- 10. Qualitative data interpretation tends to be more subjective in nature and many times can be influenced by the researcher’s biases ( Leed and Ormrod, 2001) Qualitative data requires understanding, digesting, synthesizing, conceptualizing descriptions of feelings, behaviors, experiences and ideas.
- 11. Interpreting numerical data or Quantitative data in order to make predictions is known as inferential statistics. Some measures used in inferential statistics include the standard error of the mean, estimators and the p-value.
- 12. Techniques in Interpreting Research Results • Give reasonable explanations of the relations found. • Find out the thread of uniformity that lies under the surface layer of diversified research findings.
- 13. Expected vs. Unexpected Results
- 14. Do you consider negative results as equivalent to bad results? Yes or No Questions: How will you deal with unexpected results?
- 15. A contradictory result does not mean that the study is bad or incorrect, but it suggest the idea of further investigation. An unexpected result maybe attributed to the research methodology- the research design, sampling procedure, the research instrument, data gathering procedure and statistical treatment.
Editor's Notes
- The way data is interpreted can have varying effects on the conclusion. It can be the most important key in proving or disproving the hypothesis. Whether the result is expected or unexpected, it is imperative that the researcher should give its interpretation.
- Efforts must be put into the data collection process to eliminate bias including collecting more than one kind of data, get many different kinds of perspectives on the events being studied, purposely look for contradicting informations and acknowledging your biases that relate to your research report.
- It is easy to interpret expected results because the researcher is ready for it.
- Even positive results are not exempted from having their quality questioned. Negative results can indicate novel findings or unexpected outcomes of rigorous investigations, directly or indirectly contributing to scientific discovery.