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Compilation and interpretation of primary and secondary sources of information. The integration of different sources will consolidate the write up of the report.
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Sampling techniques and types
The document discusses different sampling techniques and sample types used in research studies. It describes key concepts like target population, study population, and sampling frame. There are two main types of sampling techniques - probability sampling and non-probability sampling. Probability sampling aims to achieve a representative sample and includes random sampling, stratified random sampling, cluster sampling, and systematic sampling. Non-probability sampling includes convenience sampling, purposive sampling, and quota sampling. The document provides details on several specific sampling strategies under qualitative research.
Research Report
This document provides information about writing research reports. It discusses the various sections and formats of a research report. The main sections include the preliminary section with title page, table of contents etc., the main body with chapters introducing the topic, reviewing related literature, describing the methodology and presenting data analysis, and the references section. The chapters in the main body are structured with headings and subheadings. The methodology chapter explains the research design, sample, tools used for data collection and the statistical techniques. The data analysis chapter presents the findings in tables and uses statistical tests like t-test, ANOVA etc. Formatting guidelines and things to avoid in academic writing are also mentioned.
Methods of data collection
This document discusses various methods for collecting primary and secondary data. It describes observation, interviews, questionnaires, and schedules as the main methods for collecting primary data. It provides details on the types, advantages, and disadvantages of each method. It also discusses other techniques like surveys, audits, and panels. For secondary data, it notes that this involves using already available data from sources like governments, organizations, and past research. The key methods are summarized in 3 sentences or less.
Data collection
This document discusses data collection in quantitative studies. It explains that data are facts that provide information about the phenomenon being studied. There are several steps to collecting data quantitatively: identifying data needs like variables to measure or hypotheses to test; selecting appropriate measurement tools; pretesting instruments; developing data collection forms and procedures; implementing a data collection plan including selecting and training personnel; and addressing issues that may arise during the process like maintaining controls. The goal is to gather information consistently and validly to address the research questions.
Data collection in quantitative research
The document provides an overview of the quantitative research process. It discusses key aspects of quantitative research including descriptive, correlational, quasi-experimental, and experimental research designs. Frameworks, variables, sampling, data collection methods like questionnaires and SPSS, and analysis are also covered. The last section outlines the typical steps in quantitative research including defining the problem, reviewing literature, developing objectives and hypotheses, collecting and analyzing data, and communicating findings.
Data collection tools and technique
the mention slide is related to the data collection tools and technique and the steps of data collection
Methods of data collection (research methodology)
Included all types of data collection.Includes primary data collection and secondary data collection. Described each and every classification of Data collections which are included in KTU Kerala.
Primary & Secondary Data
This document discusses primary and secondary data sources. It defines primary data as original data collected directly for the research project, while secondary data is data collected previously for another purpose. The document outlines advantages and disadvantages of both primary and secondary data. Primary data is more accurate but costly and time-consuming to collect, while secondary data is quicker and cheaper to obtain but may not be suitable or accurate for the research purpose. The document also categorizes different types of secondary data sources such as internal company data, published materials, computer databases, and syndicated services that collect standardized data from consumers or institutions.
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Sampling techniques and types
The document discusses different sampling techniques and sample types used in research studies. It describes key concepts like target population, study population, and sampling frame. There are two main types of sampling techniques - probability sampling and non-probability sampling. Probability sampling aims to achieve a representative sample and includes random sampling, stratified random sampling, cluster sampling, and systematic sampling. Non-probability sampling includes convenience sampling, purposive sampling, and quota sampling. The document provides details on several specific sampling strategies under qualitative research.
Research Report
This document provides information about writing research reports. It discusses the various sections and formats of a research report. The main sections include the preliminary section with title page, table of contents etc., the main body with chapters introducing the topic, reviewing related literature, describing the methodology and presenting data analysis, and the references section. The chapters in the main body are structured with headings and subheadings. The methodology chapter explains the research design, sample, tools used for data collection and the statistical techniques. The data analysis chapter presents the findings in tables and uses statistical tests like t-test, ANOVA etc. Formatting guidelines and things to avoid in academic writing are also mentioned.
Methods of data collection
This document discusses various methods for collecting primary and secondary data. It describes observation, interviews, questionnaires, and schedules as the main methods for collecting primary data. It provides details on the types, advantages, and disadvantages of each method. It also discusses other techniques like surveys, audits, and panels. For secondary data, it notes that this involves using already available data from sources like governments, organizations, and past research. The key methods are summarized in 3 sentences or less.
Data collection
This document discusses data collection in quantitative studies. It explains that data are facts that provide information about the phenomenon being studied. There are several steps to collecting data quantitatively: identifying data needs like variables to measure or hypotheses to test; selecting appropriate measurement tools; pretesting instruments; developing data collection forms and procedures; implementing a data collection plan including selecting and training personnel; and addressing issues that may arise during the process like maintaining controls. The goal is to gather information consistently and validly to address the research questions.
Data collection in quantitative research
The document provides an overview of the quantitative research process. It discusses key aspects of quantitative research including descriptive, correlational, quasi-experimental, and experimental research designs. Frameworks, variables, sampling, data collection methods like questionnaires and SPSS, and analysis are also covered. The last section outlines the typical steps in quantitative research including defining the problem, reviewing literature, developing objectives and hypotheses, collecting and analyzing data, and communicating findings.
Data collection tools and technique
the mention slide is related to the data collection tools and technique and the steps of data collection
Methods of data collection (research methodology)
Included all types of data collection.Includes primary data collection and secondary data collection. Described each and every classification of Data collections which are included in KTU Kerala.
Primary & Secondary Data
This document discusses primary and secondary data sources. It defines primary data as original data collected directly for the research project, while secondary data is data collected previously for another purpose. The document outlines advantages and disadvantages of both primary and secondary data. Primary data is more accurate but costly and time-consuming to collect, while secondary data is quicker and cheaper to obtain but may not be suitable or accurate for the research purpose. The document also categorizes different types of secondary data sources such as internal company data, published materials, computer databases, and syndicated services that collect standardized data from consumers or institutions.
Methods of data collection
This document discusses various methods of data collection. It describes primary data collection methods like personal interviews, questionnaires, and observation. It also discusses secondary data collection from published sources like government publications and commercial research, as well as unpublished sources. The key differences between primary and secondary data are described, such as primary data being real-time while secondary data is from the past. Popular data storage methods include databases, spreadsheets, and statistical programs. The document emphasizes that the best data collection method depends on the research problem and available resources.
Sampling
This document discusses sampling methods and their key aspects. It defines sampling as selecting a subset of individuals from a population to make inferences about the whole population. Probability sampling methods aim to give all population elements an equal chance of selection, while non-probability methods do not. Some common probability methods described include simple random sampling, systematic sampling, and stratified sampling. The document also discusses sampling frames, statistics versus parameters, confidence levels, and evaluating different sampling techniques.
Non-Probability sampling
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Sampling in research
This document provides an overview of sampling techniques used in research. It defines key terms like population, sample, and sampling. It discusses characteristics of good sampling like being representative and free from bias. Probability sampling techniques like simple random sampling, stratified sampling, and systematic sampling are explained. Advantages of sampling like reducing time and costs are highlighted. The document outlines the sampling process and essentials of sampling. Types of sampling and various sampling methods are also summarized.
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.
SAMPLING
This document discusses sampling methods used in research. It defines sampling as obtaining information from a subset of a larger population. The key sections cover the sampling process, types of sampling including probability and non-probability methods, sources of sampling error, and factors to consider when determining sample size such as the nature of the population, number of variables, desired accuracy level, and available finances. Probability methods like simple random and stratified sampling aim to give all population members an equal chance of selection, while non-probability techniques like convenience and snowball sampling do not. Sample size is an important factor in controlling random error.
Sources of data cllection
The document discusses primary and secondary data collection techniques. It defines primary data as original data collected specifically for the research purpose, while secondary data is data that has already been collected from other sources. Some primary data collection techniques mentioned include questionnaires, surveys, observations, and interviews. Secondary data sources include published printed materials like books and journals, as well as published electronic sources like websites and databases. The advantages of secondary data include lower costs and immediate availability, while disadvantages include potential incompleteness and lack of timeliness. The document also discusses indicators, which are variables that help measure changes, and describes characteristics like validity, objectivity, sensitivity and specificity that make for ideal indicators.
Data Collection
This document discusses various methods for collecting data in research studies. It outlines the differences between quantitative and qualitative research methods. Some key methods discussed include interviews, focus groups, observation, questionnaires, and secondary data collection. Interviews can be structured, unstructured, or semi-structured. Focus groups involve a moderator guiding discussion among similar participants. Observation methods include controlled observation, naturalistic observation, and participant observation. Questionnaires can be self-administered or involve personal interviews. Secondary data is existing unpublished or published information from various sources. The document provides guidance on using these different techniques for collecting both primary and secondary data.
Data and its Types
This document discusses different types of data including:
- Qualitative data which describes attributes that can be observed but not computed, and quantitative data which can be measured numerically.
- Primary data is collected first-hand for a specific purpose, while secondary data has already been collected in the past.
- Discrete data takes only certain values, while continuous data can take any value in a range.
Research Design
This document provides information on research design. It begins by defining research design and its key elements. Research design aims to combine relevance to the research purpose with economy in procedure. It indicates decisions regarding what, where, when, how much, and by what means for a research study.
The document then discusses the need for research design, which includes facilitating smooth research operations, minimizing bias and maximizing reliability of results, providing guidance to researchers, and preventing misleading conclusions without a design. Key features of a good research design are also outlined.
Finally, the document outlines different types of research design including exploratory, descriptive, diagnostic, experimental, laboratory experiments, and field experiments. The differences between exploratory and descriptive research designs
Design of qualitative research
This document discusses the key aspects of qualitative research design. It explains that qualitative research relies on data from interviews, observations, and documents rather than testing hypotheses. The goal is to understand people's behaviors and meanings rather than measuring things. Some common qualitative designs mentioned are grounded theory, ethnography, phenomenology, case studies, and content analysis. Sample sizes are small and purposeful rather than random. Data collection methods include interviews, observations, and documents. Analysis uses an inductive approach to identify themes. Researchers are the main instrument and context is important for understanding findings.
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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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Sampling techniques
The document discusses sampling design and methods. It defines key terms like universe, population, sample, and stratum. There are several advantages to sampling like collecting information more quickly and at lower cost compared to a full census. Probability sampling ensures each unit has a known chance of selection, while non-probability sampling does not. Specific probability sampling methods discussed include simple random sampling, where each unit has an equal chance of selection, and stratified random sampling, where the population is divided into subgroups and samples are drawn from each.
Sampling techniques
This document provides an overview of sampling techniques. It defines key sampling terms like population, sample, sampling frame, and discusses the need for sampling due to constraints of time and money for a full census. The document outlines different sampling methods like simple random sampling, stratified sampling, cluster sampling and multistage sampling. It also discusses non-probability sampling techniques like convenience sampling and snowball sampling. The document emphasizes the importance of representativeness, adequacy and independence for a good sample. It concludes by noting sources of error in sampling like sampling errors and non-sampling errors.
Non- Probability Sampling & Its Methods
A detailed explanation of non-probability sampling and its methods have been covered. There are 4 types of non- probability sampling methods:
1. convenience sampling
2. purposive sampling
3. quota sampling (both controlled and uncontrolled)
4. snowball sampling (all 3 ways of performing)
Meaning with adequate examples, pros and cons have been covered
For and query or further information, Kindly contact:
Arpit Surana
https://www.linkedin.com/in/arpitsurana116/
arpitsurana116116@gmail.com
Data Interpretation
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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Chapter 11 Data Analysis Classification and Tabulation
Data analysis involves classifying and tabulating data to identify relationships and make inferences. There are two main types of data analysis: qualitative analysis which handles categorical data, and quantitative analysis which uses statistical methods on numerical data. The goals of data analysis are to understand the data, answer research questions, identify patterns, and make predictions. Key aspects of data analysis include variables, attributes, parametric vs non-parametric statistics, classification methods, and tabulation which organizes data into tables.
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This document provides an overview of research writing and summarizes the typical contents and structure of a research report. It discusses the preliminary parts of a report such as the title page and table of contents. It also outlines the main body of the report including typical chapters for the introduction, literature review, research methodology, data presentation and analysis, and summary and conclusions. Finally, it notes that supplementary sections may include references, bibliography, and appendices.
Academic Report Writing - Complete Lesson
The document outlines the course syllabus and schedule for an Advanced English for Academic Communication course. It provides details on coursework requirements and marking breakdown. It then covers topics to be discussed each weekend, including research planning, proposal presentation, data collection and analysis, report writing, and oral presentations. Guidance is given on conducting research, writing research proposals, collecting and analyzing primary and secondary data, writing research reports, and delivering oral presentations. Key aspects like literature reviews, methodology, findings and discussion, and conclusion and recommendations are also explained.
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This document discusses various methods of data collection. It describes primary data collection methods like personal interviews, questionnaires, and observation. It also discusses secondary data collection from published sources like government publications and commercial research, as well as unpublished sources. The key differences between primary and secondary data are described, such as primary data being real-time while secondary data is from the past. Popular data storage methods include databases, spreadsheets, and statistical programs. The document emphasizes that the best data collection method depends on the research problem and available resources.
Sampling
This document discusses sampling methods and their key aspects. It defines sampling as selecting a subset of individuals from a population to make inferences about the whole population. Probability sampling methods aim to give all population elements an equal chance of selection, while non-probability methods do not. Some common probability methods described include simple random sampling, systematic sampling, and stratified sampling. The document also discusses sampling frames, statistics versus parameters, confidence levels, and evaluating different sampling techniques.
Non-Probability sampling
Having Population and Sampling definitions, Advantages and Disadvantages of Sampling, Details of Non-Probability Sampling
Sampling in research
This document provides an overview of sampling techniques used in research. It defines key terms like population, sample, and sampling. It discusses characteristics of good sampling like being representative and free from bias. Probability sampling techniques like simple random sampling, stratified sampling, and systematic sampling are explained. Advantages of sampling like reducing time and costs are highlighted. The document outlines the sampling process and essentials of sampling. Types of sampling and various sampling methods are also summarized.
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.
SAMPLING
This document discusses sampling methods used in research. It defines sampling as obtaining information from a subset of a larger population. The key sections cover the sampling process, types of sampling including probability and non-probability methods, sources of sampling error, and factors to consider when determining sample size such as the nature of the population, number of variables, desired accuracy level, and available finances. Probability methods like simple random and stratified sampling aim to give all population members an equal chance of selection, while non-probability techniques like convenience and snowball sampling do not. Sample size is an important factor in controlling random error.
Sources of data cllection
The document discusses primary and secondary data collection techniques. It defines primary data as original data collected specifically for the research purpose, while secondary data is data that has already been collected from other sources. Some primary data collection techniques mentioned include questionnaires, surveys, observations, and interviews. Secondary data sources include published printed materials like books and journals, as well as published electronic sources like websites and databases. The advantages of secondary data include lower costs and immediate availability, while disadvantages include potential incompleteness and lack of timeliness. The document also discusses indicators, which are variables that help measure changes, and describes characteristics like validity, objectivity, sensitivity and specificity that make for ideal indicators.
Data Collection
This document discusses various methods for collecting data in research studies. It outlines the differences between quantitative and qualitative research methods. Some key methods discussed include interviews, focus groups, observation, questionnaires, and secondary data collection. Interviews can be structured, unstructured, or semi-structured. Focus groups involve a moderator guiding discussion among similar participants. Observation methods include controlled observation, naturalistic observation, and participant observation. Questionnaires can be self-administered or involve personal interviews. Secondary data is existing unpublished or published information from various sources. The document provides guidance on using these different techniques for collecting both primary and secondary data.
Data and its Types
This document discusses different types of data including:
- Qualitative data which describes attributes that can be observed but not computed, and quantitative data which can be measured numerically.
- Primary data is collected first-hand for a specific purpose, while secondary data has already been collected in the past.
- Discrete data takes only certain values, while continuous data can take any value in a range.
Research Design
This document provides information on research design. It begins by defining research design and its key elements. Research design aims to combine relevance to the research purpose with economy in procedure. It indicates decisions regarding what, where, when, how much, and by what means for a research study.
The document then discusses the need for research design, which includes facilitating smooth research operations, minimizing bias and maximizing reliability of results, providing guidance to researchers, and preventing misleading conclusions without a design. Key features of a good research design are also outlined.
Finally, the document outlines different types of research design including exploratory, descriptive, diagnostic, experimental, laboratory experiments, and field experiments. The differences between exploratory and descriptive research designs
Design of qualitative research
This document discusses the key aspects of qualitative research design. It explains that qualitative research relies on data from interviews, observations, and documents rather than testing hypotheses. The goal is to understand people's behaviors and meanings rather than measuring things. Some common qualitative designs mentioned are grounded theory, ethnography, phenomenology, case studies, and content analysis. Sample sizes are small and purposeful rather than random. Data collection methods include interviews, observations, and documents. Analysis uses an inductive approach to identify themes. Researchers are the main instrument and context is important for understanding findings.
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.
Sampling ,types ,advantages and disadvantages of the sampling
introduction and the types of the sampling , advantages of the sampling and disadvantages of sampling
Sampling techniques
The document discusses sampling design and methods. It defines key terms like universe, population, sample, and stratum. There are several advantages to sampling like collecting information more quickly and at lower cost compared to a full census. Probability sampling ensures each unit has a known chance of selection, while non-probability sampling does not. Specific probability sampling methods discussed include simple random sampling, where each unit has an equal chance of selection, and stratified random sampling, where the population is divided into subgroups and samples are drawn from each.
Sampling techniques
This document provides an overview of sampling techniques. It defines key sampling terms like population, sample, sampling frame, and discusses the need for sampling due to constraints of time and money for a full census. The document outlines different sampling methods like simple random sampling, stratified sampling, cluster sampling and multistage sampling. It also discusses non-probability sampling techniques like convenience sampling and snowball sampling. The document emphasizes the importance of representativeness, adequacy and independence for a good sample. It concludes by noting sources of error in sampling like sampling errors and non-sampling errors.
Non- Probability Sampling & Its Methods
A detailed explanation of non-probability sampling and its methods have been covered. There are 4 types of non- probability sampling methods:
1. convenience sampling
2. purposive sampling
3. quota sampling (both controlled and uncontrolled)
4. snowball sampling (all 3 ways of performing)
Meaning with adequate examples, pros and cons have been covered
For and query or further information, Kindly contact:
Arpit Surana
https://www.linkedin.com/in/arpitsurana116/
arpitsurana116116@gmail.com
Data Interpretation
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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Processing & Analysis of Data, Data editing, Benefits of data editing, Data coding, Classification of data, CLASSIFICATION ACCORDING THE ATTRIBUTES, CLASSIFICATION ON THE BASIS OF INTERVAL, TABULATION of data, Types of tables, Graphing of data, Bar chart, Pie chart, Line graph, histogram, Polygon / ogive, Analysis of Data, Descriptive Analysis, Uni-Variate Analysis, Bivariate Analysis, Multi-Variate Analysis, Causal Analysis, Inferential Analysis, PARAMETRIC TESTS, Non parametric Test,
Chapter 11 Data Analysis Classification and Tabulation
Data analysis involves classifying and tabulating data to identify relationships and make inferences. There are two main types of data analysis: qualitative analysis which handles categorical data, and quantitative analysis which uses statistical methods on numerical data. The goals of data analysis are to understand the data, answer research questions, identify patterns, and make predictions. Key aspects of data analysis include variables, attributes, parametric vs non-parametric statistics, classification methods, and tabulation which organizes data into tables.
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Data analysis
This document provides an overview of research writing and summarizes the typical contents and structure of a research report. It discusses the preliminary parts of a report such as the title page and table of contents. It also outlines the main body of the report including typical chapters for the introduction, literature review, research methodology, data presentation and analysis, and summary and conclusions. Finally, it notes that supplementary sections may include references, bibliography, and appendices.
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The document outlines the course syllabus and schedule for an Advanced English for Academic Communication course. It provides details on coursework requirements and marking breakdown. It then covers topics to be discussed each weekend, including research planning, proposal presentation, data collection and analysis, report writing, and oral presentations. Guidance is given on conducting research, writing research proposals, collecting and analyzing primary and secondary data, writing research reports, and delivering oral presentations. Key aspects like literature reviews, methodology, findings and discussion, and conclusion and recommendations are also explained.
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An outline of the major components of the research proposal:
Cover Page:
Title (A case study of …….)
Purpose why the research is conducted
Name and Address of the investigator (Student researcher)
Name and Address of the advisor
Logo
Month and Place where the proposal is written
Acknowledgement
Table of Contents
List of Tables
List of Figures
List of Acronyms
Background of the study: General to specific or deductive order is recommended
Statement of the problem: (Justification of the study)
Research Objectives, Research Questions, and Research Hypothesis:
1.3.1 Research Objectives – Ends to be met in conducting the research
This shows what the investigator will analyze and how;
What comparisons to make and at what level
General Objective: Often one statement directly related to the topic.
Specific Objectives: Often 3-5;
What the researcher want to achieve
What to analyze and compare
1.3.2 Research Questions – Questions to be answered to meet the research objectives or produce implications of the hypothesis.
1.3.3 Research Hypothesis (Optional) – Tentative propositions to be tested in the research.
1.4 Research Methodology:
1.4.1 Data Type and Source (Decide one of them or both by giving justifications)
Qualitative V/s Quantitative (Give reasons)
Primary Sources (Decide on which method or methods to use by stating justifiable reasons)
Questionnaires
Interviews
Observations
Focus group discussions
Secondary Sources (Decide on which method or methods to use by stating justifiable reasons) and exactly state the sources from which you will get the data.
-Reports, manuals, internal publications, data base systems, Journals and Publications for assessing existing findings and internet.
-Books for assessing theories and principles related to the topic etc.
1.4.2 Study design:
Census V/s Survey (Decide which one to use and why?).
Survey Design (Decide on the survey designs to be used by investigator clearly stating the reasons for your decision).
Sample Size (Use the sample size determinations formula as a base and make adjustments with due regard to the target population and the homogeneity or heterogeneity of the population characteristics).
Sampling Design (Show how and why you are going to use the different techniques of probability and/or non-probability sampling techniques).
1.4.3 Data Collection:
State the data collection tool or tools to be used with necessary justifications written in the proposal.
Questionnaire design
Questionnaire testing or pretesting if necessary
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Secondary methods involve using existing data collected by others. Common secondary sources include publications, reports, and data available online. While cheaper and faster
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1. The document discusses various topics related to data processing and analysis including defining data and information, the steps of data processing, types of data processing, what data analysis is, important types of data analysis methods, and qualitative study design and data analysis approaches.
2. It provides details on data editing, coding, classification, entry, validation, and tabulation as steps in data processing. Common statistical packages, tools, and software for data analysis are also outlined.
3. Qualitative research methods and coding systems are explained as well as qualitative data analysis software packages that can be used.
Research Methodology
The document outlines key aspects of research methodology including:
1. The objectives of research such as defining problems, formulating hypotheses, collecting and evaluating data, making deductions, and testing conclusions.
2. The different types of research including descriptive, applied, quantitative, conceptual, empirical, qualitative, fundamental, and analytical research.
3. The methods of collecting data including primary methods like questionnaires, observations, interviews, and schedules and secondary methods of collecting published and unpublished data from various sources.
DATA COLLECTION METHODS PRESENTATION ( EMMANUEL SIAW OKAI).pdf
This document provides an overview of data collection methods for research. It discusses primary and secondary sources of data, as well as various methods for collecting each type. For secondary data, common sources include published books, articles, and online sources. Primary data is collected directly by the researcher through methods like surveys, interviews, focus groups, observations, and case studies. Both primary and secondary data collection have benefits like saving time and money, but also drawbacks like inappropriate or incomplete data. The document concludes with examples of structured interviews and questionnaires that could be used for primary data collection.
BRM_Lecture 4 PPT.pptx
The document outlines the 11 main steps in the research process: 1) selecting and formulating a research problem, 2) conducting an extensive literature review, 3) developing objectives, 4) identifying and measuring variables, 5) setting hypotheses, 6) writing a synopsis, 7) designing the research, 8) collecting data, 9) analyzing and interpreting data using statistics, 10) testing hypotheses, and 11) preparing and presenting the final report. These steps provide a framework for researchers to systematically plan, execute, analyze, and communicate their work.
PROCESS OF RESEARCH
The document outlines the key steps in the business research process:
1. Data collection, which can involve primary or secondary sources. Primary data is directly collected while secondary data refers to existing information.
2. Data analysis and interpretation to assign meaning and conclusions to the findings.
3. Research reporting to summarize the research process, findings, recommendations, and other important details in a well-crafted document.
3. TYPES OF REPORTS.pptx
A report is a formal document written for various purposes in sciences, social sciences, engineering, and business. There are three main types of reports: analytical reports which analyze a situation and provide conclusions and recommendations; informative reports which provide details without analysis; and persuasive reports which aim to sell an idea or product. Reports can also be categorized as short reports which are concise and to the point, or long reports which provide more extensive analysis. Common types of short reports include progress reports, field study reports, accident/incident reports, and laboratory reports. Short reports should include the purpose, findings, conclusions, and recommendations.
Research Report
Writing a research report involves four main steps:
1. Preparing by identifying the purpose, aims, and research question.
2. Collecting and organizing information from primary sources like experiments and secondary sources like other research.
3. Planning the report structure with headings, sections, and logical organization before writing.
4. Writing the report by including key sections like the title page, abstract/executive summary, introduction, methodology, results, discussion, conclusion, and references. The report should be logically organized and written to clearly communicate the research to the reader.
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Examples of nursing exam (snle ) 3
1. This document contains 10 multiple choice nursing questions and answers related to caring for patients with immune disorders, rheumatoid arthritis, osteoarthritis, and herpes zoster.
2. The questions cover topics like identifying the stage of HIV infection based on symptoms and CD4 count, common symptoms of immunodeficiency, appropriate nursing diagnoses and interventions for patients with joint disorders, and the diagnostic test used to confirm herpes zoster.
3. The questions are meant to test nursing knowledge of assessing, diagnosing, and planning care for patients with various immune and musculoskeletal conditions.
Examples of nursing exam (snle ) 2
1. The document contains sample questions and answers from a nursing exam about adult nursing care and renal/urinary disorders.
2. The questions cover topics like normal lab values related to renal function, assessing patients with urinary disorders, common causes of urinary tract infections, and key nursing considerations when caring for patients with renal issues.
3. The answer explanations provide rationales for each response based on assessing renal function, typical etiologies, appropriate diagnostic tests, and important nursing assessments and interventions for related conditions.
Examples of nursing exam (snle )1
This document contains 10 multiple choice questions about urology and ophthalmology disorders for a nursing exam. The questions cover topics like risk factors and management of conditions like urolithiasis, polycystic kidney disease, renal angiography complications, and eye disorders including cataracts, detached retinas, corneal ulcers, and glaucoma. The questions assess knowledge of appropriate dietary recommendations, symptoms, appropriate nursing interventions, and pre-operative teaching points.
Unrology system disorders quesions and answers
The document contains a quiz on the renal and urinary system with questions covering topics like the main structures, urine formation, normal urine characteristics, bladder capacity, urinary retention, renal failure, kidney diseases, cancers, infections, and incontinence. It tests knowledge of kidney and bladder anatomy and physiology as well as common diseases and disorders that can affect this system.
Renal disorders quesions and answers with rationals
This document contains 13 multiple choice questions about renal disorders and care of clients with renal issues. It provides the questions, possible answer choices, and a rationale for the correct answer. The questions cover topics like interpreting lab values related to renal function, dietary management for clients on hemodialysis, emergency interventions for potential complications of hemodialysis like air embolism, and assessing clients for possible bladder trauma. The rationales provided explain why each correct answer choice is most appropriate based on considerations like normal lab value ranges and priority nursing actions.
Upper gi tract bleeding
Upper GI tract bleeding is commonly caused by gastritis or peptic ulcer disease and presents with hematemesis, melena, and symptoms of blood loss like faintness or changes in vital signs. Management involves correcting blood loss to prevent shock, monitoring the patient closely, testing for blood, and noting urine output. Surgery may be required if bleeding recurs within 48 hours or if transfusions of more than 6-10 units of blood are needed in 24 hours.
Esophageal varices
Esophageal varices develop from elevated venous pressure in the portal system and may rupture, causing bleeding in the upper and lower gastrointestinal tract with a high mortality rate. Diagnosis involves endoscopy to identify the site of bleeding. Medical management focuses on stabilizing vital signs if bleeding occurs and administering drugs and fluids to decrease portal pressure and replace fluid losses. Treatment options include band ligation, which is the treatment of choice, as well as sclerotherapy and use of a Sengstaken-Blakemore tube to control hemorrhaging. General nursing care centers around rest, nutrition, hygiene and comfort measures.
Nursing pharmacology part2
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Nursing pharmacology part1
This document provides an overview of pharmacology topics for nurses, including the nursing process in pharmacology, drug names, pharmacology basics, educating patients, drug interactions, routes of administration, considerations across the life span, and schedules of controlled substances. It discusses assessing, analyzing, planning, implementing, and evaluating the nursing care related to drug administration and monitoring therapeutic and adverse effects. Key aspects of pharmacokinetics, pharmacodynamics, and pharmacotherapeutics are defined. The importance of patient education on drugs is emphasized.
Carpal tunnel syndrome
Carpal Tunnel Syndrome occurs when repetitive hand and wrist movements compress the median nerve at the wrist, causing night pain, numbness, and a positive Tinel's sign. Management involves giving corticosteroids and applying wrist splints to relieve pressure on the median nerve.
Musculoskeletal conditions, fractures
Define
Define related concepts nursing care of patients with musculoskeletal disorders.
Recognize
Recognize different types of musculoskeletal disorders.
Identify
Identify the clinical manifestations of musculoskeletal disorders.
Recognize
Recognize the medical management of musculoskeletal disorders.
Recognize
Recognize the nursing management
patients with musculoskeletal disorders.
Metabolic bone disorders
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Bone tumor
Bone tumors can be benign or malignant growths of bone tissue. Common sites for malignant bone tumors are the distal femur, proximal tibia, and proximal humerus. The most common and fatal malignant bone tumor is osteosarcoma, which often spreads to the lungs. Symptoms of bone tumors include localized pain in the bone, limited range of motion, weight loss, and pathologic fractures. Diagnostic tests include bone x-rays to detect the tumor and chest x-rays to check for lung metastases, with biopsy used to examine the tumor histologically. Treatment aims to destroy or remove the tumor through radiation therapy, chemotherapy, surgery such as limb-sparing procedures or amputation.
Diagnostic studies
Diagnostic studies can be either noninvasive or invasive. Noninvasive studies do not require cutting or inserting anything into the body and include x-rays, MRI, CT scans, and ultrasounds. Invasive studies require inserting devices such as for colonoscopies, upper GI endoscopies, bronchoscopies, and cystoscopies. Common imaging tests include x-rays which use radiation to create pictures of bone and tissue, MRI which uses magnets to image soft tissues, and CT scans which combine x-rays with computers to create cross-sectional images of the body.
Common diagnostic & laboratory tests
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Common diagnostic & laboratory tests and procedures
This document provides an overview of common laboratory tests and diagnostic procedures. It begins by identifying some common laboratory specimens like blood, urine, sputum, and tissues. It then describes several routine blood tests including complete blood count, blood chemistry, blood enzymes, blood clotting, and tests to assess heart disease risk. Other tests and procedures discussed include urinalysis, stool analysis, x-rays, MRI, CT scans, ultrasounds, and various endoscopic exams of organs like the colon, stomach, lungs, bladder, and airways. The goal is to familiarize students with laboratory and diagnostic tests that can identify and diagnose various health conditions.
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1. **Epidermis**: The outermost layer primarily composed of epithelial cells called keratinocytes. It provides a protective barrier against environmental factors, pathogens, and UV radiation.
2. **Dermis**: Located beneath the epidermis, the dermis contains connective tissue, blood vessels, hair follicles, and sweat glands. It plays a vital role in supporting and nourishing the epidermis, regulating body temperature, and housing sensory receptors for touch, pressure, temperature, and pain.
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CLASSIFICATION OF H1 ANTIHISTAMINICS-
FIRST GENERATION ANTIHISTAMINICS-
1)HIGHLY SEDATIVE-DIPHENHYDRAMINE,DIMENHYDRINATE,PROMETHAZINE,HYDROXYZINE 2)MODERATELY SEDATIVE- PHENARIMINE,CYPROHEPTADINE, MECLIZINE,CINNARIZINE
3)MILD SEDATIVE-CHLORPHENIRAMINE,DEXCHLORPHENIRAMINE
TRIPROLIDINE,CLEMASTINE
SECOND GENERATION ANTIHISTAMINICS-FEXOFENADINE,
LORATADINE,DESLORATADINE,CETIRIZINE,LEVOCETIRIZINE,
AZELASTINE,MIZOLASTINE,EBASTINE,RUPATADINE. Mechanism of action of 2nd generation antihistaminics-
These drugs competitively antagonize actions of
histamine at the H1 receptors.
Pharmacological actions-
Antagonism of histamine-The H1 antagonists effectively block histamine induced bronchoconstriction, contraction of intestinal and other smooth muscle and triple response especially wheal, flare and itch. Constriction of larger blood vessel by histamine is also antagonized.
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4) Anticholinergic action- many H1 blockers
in addition antagonize muscarinic actions of ACh. BUT IN 2ND gen histaminics there is Higher H1 selectivitiy : no anticholinergic side effects
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Receptor Discordance in Breast Carcinoma During the Course of Life
Definition:
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Causes:
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Genetic and epigenetic changes during tumor progression can lead to alterations in receptor status.
Treatment Effects:
Therapies, especially endocrine and targeted therapies, can selectively pressure tumor cells, causing shifts in receptor expression.
Heterogeneity:
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Impact on Treatment:
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Treatment Adjustment:
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Clinical Implications:
Prognosis:
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Data+collection+methods
- 2. Compilation and interpretation of primary and secondary sources of information. The integration of different sources will consolidate the write up of the report. DATA COLLECTION
- 3. SOURCES OF INFORMATION Primary SourcePrimary Source •Data is collected by researcher himself •Data is gathered through questionnaire, interviews, observations etc. Secondary SourceSecondary Source •Data collected, compiled or written by other researchers eg. books, journals, newspapers •Any reference must be acknowledged
- 4. STEPS TO COLLECT DATA DATA ANALYSIS AND INTERPRETATIONDATA ANALYSIS AND INTERPRETATION REVIEW & COMPILE SECONDARY SOURCE INFORMATIONREVIEW & COMPILE SECONDARY SOURCE INFORMATION (Referred to in the BACKGROUND/ INTRODUCTION section of report) REVIEW & COMPILE SECONDARY SOURCE INFORMATIONREVIEW & COMPILE SECONDARY SOURCE INFORMATION (Referred to in the BACKGROUND/ INTRODUCTION section of report) PLAN & DESIGN DATA COLLECTION INSTRUMENTSPLAN & DESIGN DATA COLLECTION INSTRUMENTS TO GATHER PRIMARY INFORMATIONTO GATHER PRIMARY INFORMATION (Referred to in the FINDINGS, CONCLUSIONS & RECOMMENDATIONS sections of report) PLAN & DESIGN DATA COLLECTION INSTRUMENTSPLAN & DESIGN DATA COLLECTION INSTRUMENTS TO GATHER PRIMARY INFORMATIONTO GATHER PRIMARY INFORMATION (Referred to in the FINDINGS, CONCLUSIONS & RECOMMENDATIONS sections of report) DATA COLLECTIONDATA COLLECTIONDATA COLLECTIONDATA COLLECTION
- 5. METHODS USED TO COLLECT PRIMARY SOURCE DATA 1. Interviews 2. Questionnaires 3. Survey 4. Experimentation 5. Case Study 6. Observation However, for a small-scale study, the most commonly used methods are interviews, survey questionnaires and observations.
- 6. Effective way of gathering information INTERVIEW Involves verbal and non-verbal communications Can be conducted face to face, by telephone, online or through mail
- 7. Steps To An Effective Interview Prepare your interview schedule Select your subjects/ key informants Conduct the interview Analyze and interpret data collected from the interview
- 8. The most common data collection instrument Survey Questionnaire Useful to collect quantitative and qualitative information Should contain 3 elements: 1. Introduction – to explain the objectives 2. Instructions – must be clear, simple language & short 3. User-friendly – avoid difficult or ambiguous questions
- 9. 2 Basic Types of survey questions: 1. Open-ended Questions Free-response (Text Open End) Fill-in relevant information 2. Close-ended Questions Dichotomous question Multiple-choice Rank Scale Categorical Numerical Note: For specific examples and students’ activities on each question style, please refer to the notes on Data Collection in the e-learning.
- 10. Steps To An Effective Survey Questionnaire Prepare your survey questions (Formulate & choose types of questions, order them, write instructions, make copies) Select your respondents/sampling Random/Selected Administer the survey questionnaire (date, venue, time ) Analyze and interpret data collected Tabulate data collected (Statistical analysis-frequency/mean/correlation/% )
- 11. Observe verbal & non-verbal communication, surrounding atmosphere, culture & situation Observations Need to keep meticulous records of the observations Can be done through discussions, observations of habits, rituals, review of documentation, experiments
- 12. Steps To An Effective Observation Determine what needs to be observed (Plan, prepare checklist, how to record data) Select your participants Random/Selected Conduct the observation (venue, duration, recording materials, take photographs ) Analyze and interpret data collected Compile data collected
- 13. DATA ANALYSIS 3. In a small scale study, the most common forms of statistical analysis presented are: •Frequency •Mean •Percentage 1. To analyse data from interviews and observation, use Summary sheet Checklist 2. To analyse data from questionnaires, use Manually SPSS
- 14. DATA INTERPRETATION 1. It involves 2 terms • ‘Results’ – presentation of data/findings (statistics) • ‘Discussion’ – interpretation of data/findings 2. Things to consider when interpreting your data: • Interpret findings based on the purpose and objectives of your study • Relate the findings to real life context • Use persuasive language to convince your readers to see the research from your point of view. • Order your interpretation to highlight the most important findings • Include limitations to your research. • Use simple, clear language
- 15. HAVE A NICE DAY