Quantitative Research Methods
1.What is scientific research? What is quantitative research?
2.Why we need research?
3.Who is conducting the research?
4.What is the research process?
5.What is the language of research?
This document summarizes a lecture on quantitative research methods. It discusses key topics like what statistics are, types of statistics (descriptive and inferential), types of research, levels of measurement, and rules for using different levels of measurement. Hands-on examples are provided on graphical descriptive techniques. Finally, different question formats for measurement like Likert scales, semantic differential scales, and others are covered. Students are assigned weekly reading and exercises analyzing data from chapters and interpreting results.
Methods of collecting data
Survey, methods and type, response rate, variable language
Hands on: Graphical techniques II, SPSS
Questionnaire design
Tips on writing a research paper
Individual project: article critique
This document summarizes key concepts from a lecture on quantitative research methods. It discusses the logic and importance of sampling, including common errors like selection bias. A classic example is provided of a polling failure in 1936 due to selecting an unrepresentative sample. The document also covers types of sampling methods like simple random sampling, stratified random sampling, systematic sampling, and cluster sampling. Probability and non-probability sampling techniques are defined. Finally, considerations for determining appropriate sample sizes are presented.
This document provides an overview of quantitative research methods and statistical analysis techniques. It discusses descriptive statistics such as frequencies, measures of central tendency, variability, and relationships. It also covers inferential statistics including t-tests, which are used to assess differences between two groups, and correlation, which examines relationships between two variables. Examples of conducting statistical tests in SPSS are provided.
This document discusses qualitative data analysis and interpretation. It describes how analysis differs between quantitative and qualitative research traditions. It also discusses strategies for analyzing qualitative data, such as identifying themes, coding data, and concept mapping. The document outlines steps for data analysis during and after data collection. It emphasizes analyzing data iteratively and interpreting findings by answering questions about importance and meaning. Finally, it discusses ensuring credibility, mixed methods research, and evaluating mixed methods designs.
Review of "Survey Research Methods & Design in Psychology"James Neill
This document provides an overview and summary of a lecture on survey research and design in psychology. It discusses key topics like the research process, survey design, data analysis, reliability and validity, sampling, and reporting results. Assessment involves a lab report on survey-based research and a final exam testing knowledge of research methods and statistical analysis techniques.
A must see for graduate students. This presentation describes how to conduct common quantitative statistical analyses, interpret the results, and present them in APA format. Dr. James Lani covers both quantitative and qualitative analyses, such as: descriptive statistics, chi-square, pearson correlation, t-test, ANOVA, regression, mediation, and moderation. He also discusses grounded theory and phenomenological analysis
SSP is now Intellectus Statistics Software. Intellectus Statistics™ software primarily serves the academic and research communities as a powerful statistical package that can be purchased via four distinct cloud based subscriptions. Learn more here: http://www.statisticssolutions.com/buy-intellectus/
In this webinar Dr. Lani discusses key points in successfully completing your quantitative analysis. You will learn how to conduct common statistical analyses, how to examine assumptions, how to easily generate APA 6th edition tables and figures, how to use Intellectus Statistics(TM) Software, how to identify and interpret the appropriate statistics, and how to present and summarize your findings.
SSP is now Intellectus Statistics Software. Intellectus Statistics™ software primarily serves the academic and research communities as a powerful statistical package that can be purchased via four distinct cloud based subscriptions. Learn more here: http://www.statisticssolutions.com/buy-intellectus/
This document summarizes a lecture on quantitative research methods. It discusses key topics like what statistics are, types of statistics (descriptive and inferential), types of research, levels of measurement, and rules for using different levels of measurement. Hands-on examples are provided on graphical descriptive techniques. Finally, different question formats for measurement like Likert scales, semantic differential scales, and others are covered. Students are assigned weekly reading and exercises analyzing data from chapters and interpreting results.
Methods of collecting data
Survey, methods and type, response rate, variable language
Hands on: Graphical techniques II, SPSS
Questionnaire design
Tips on writing a research paper
Individual project: article critique
This document summarizes key concepts from a lecture on quantitative research methods. It discusses the logic and importance of sampling, including common errors like selection bias. A classic example is provided of a polling failure in 1936 due to selecting an unrepresentative sample. The document also covers types of sampling methods like simple random sampling, stratified random sampling, systematic sampling, and cluster sampling. Probability and non-probability sampling techniques are defined. Finally, considerations for determining appropriate sample sizes are presented.
This document provides an overview of quantitative research methods and statistical analysis techniques. It discusses descriptive statistics such as frequencies, measures of central tendency, variability, and relationships. It also covers inferential statistics including t-tests, which are used to assess differences between two groups, and correlation, which examines relationships between two variables. Examples of conducting statistical tests in SPSS are provided.
This document discusses qualitative data analysis and interpretation. It describes how analysis differs between quantitative and qualitative research traditions. It also discusses strategies for analyzing qualitative data, such as identifying themes, coding data, and concept mapping. The document outlines steps for data analysis during and after data collection. It emphasizes analyzing data iteratively and interpreting findings by answering questions about importance and meaning. Finally, it discusses ensuring credibility, mixed methods research, and evaluating mixed methods designs.
Review of "Survey Research Methods & Design in Psychology"James Neill
This document provides an overview and summary of a lecture on survey research and design in psychology. It discusses key topics like the research process, survey design, data analysis, reliability and validity, sampling, and reporting results. Assessment involves a lab report on survey-based research and a final exam testing knowledge of research methods and statistical analysis techniques.
A must see for graduate students. This presentation describes how to conduct common quantitative statistical analyses, interpret the results, and present them in APA format. Dr. James Lani covers both quantitative and qualitative analyses, such as: descriptive statistics, chi-square, pearson correlation, t-test, ANOVA, regression, mediation, and moderation. He also discusses grounded theory and phenomenological analysis
SSP is now Intellectus Statistics Software. Intellectus Statistics™ software primarily serves the academic and research communities as a powerful statistical package that can be purchased via four distinct cloud based subscriptions. Learn more here: http://www.statisticssolutions.com/buy-intellectus/
In this webinar Dr. Lani discusses key points in successfully completing your quantitative analysis. You will learn how to conduct common statistical analyses, how to examine assumptions, how to easily generate APA 6th edition tables and figures, how to use Intellectus Statistics(TM) Software, how to identify and interpret the appropriate statistics, and how to present and summarize your findings.
SSP is now Intellectus Statistics Software. Intellectus Statistics™ software primarily serves the academic and research communities as a powerful statistical package that can be purchased via four distinct cloud based subscriptions. Learn more here: http://www.statisticssolutions.com/buy-intellectus/
The presentation covered key steps in analyzing survey data including defining goals, designing valid and reliable survey questions, collecting data, cleaning data, conducting descriptive statistics and correlations, comparing mean differences between groups, and clearly presenting results along with conclusions and recommendations. Piloting surveys and continuously improving methods was also emphasized.
Regardless of which strategies used by researcher to present their qualitative data, the presentation will result in identifying and acknowledging the multiple perspectives of the participants and researcher and the readers may then consider all perspectives in their interpretation of the research. This Slideshare provides information, strategies and references on how qualitative data could be presented.
The document discusses the process of data preparation, which involves validating raw data collected through surveys or observations to ensure it is accurate and unbiased. The key steps in data preparation are data validation, editing and coding, data entry, and data tabulation. Data validation aims to detect any fraud, screening errors, issues with data collection procedures, or incomplete responses. Descriptive statistics such as measures of central tendency (mean, median, mode) and variability (range, variance, standard deviation) are then used to analyze the prepared data. Graphs are also employed to visually depict patterns in the data.
This document discusses various sampling methods used in business research. It covers probability sampling techniques like simple random sampling, systematic sampling, stratified sampling, cluster sampling, and multistage sampling. It also discusses non-probability sampling techniques such as convenience sampling, quota sampling, and judgmental sampling. The key factors in determining sample size are described as the nature of the population, desired level of accuracy, available resources, and characteristics of the sampling method. Methods to reduce sampling errors like measurement, consistency checks, and quality control are also summarized.
Having systematic questionnaire design and testing procedures in place is vital for data quality,
particularly for a minimisation of the measurement error.
The document discusses the importance of rigor and robustness in research. It aims to provide insight into the meaning of rigor and how it can be maintained throughout the different stages of the research process, regardless of the research approach or paradigm used. Specifically, it discusses strategies for achieving rigor in areas like sampling techniques, data collection, data analysis, and reporting findings. Maintaining rigor is important for producing robust and reliable research results.
The document provides an overview of key aspects of survey design, including question styles, response formats, sampling, and implementation. It discusses developing a questionnaire, types of questions, optimizing question wording and structure, pre-testing surveys, and sampling techniques. The goal is to introduce rigorous methodology to plan, develop, and implement effective research questionnaires.
This document provides an overview of key concepts in descriptive statistics and intelligence testing including:
1. It describes four scales of measurement: nominal, ordinal, ratio, and equal-interval. It also discusses distributions, measures of central tendency, and measures of dispersion.
2. It discusses norms-referenced and criterion-referenced assessment. It also covers reliability, validity, and factors that can affect accurate assessment such as accommodations for students with disabilities.
3. It provides an overview of intelligence tests and behaviors they sample. It notes the dilemmas in assessing intelligence and describes some commonly used individual intelligence tests.
This document discusses various topics related to data analysis and hypothesis testing in business research methods. It covers data processing operations like editing, coding, classification and tabulation. It also discusses various graphical representations of data like bar charts, pie charts, histograms and their appropriate usage. The document then explains the concepts of hypothesis, null hypothesis and alternative hypothesis. It describes hypothesis testing logic and the concepts of type 1 and type 2 errors. It lists the steps involved in hypothesis testing like setting up the hypothesis, determining test statistics, critical regions, and making decisions.
The document provides an overview of quantitative and qualitative data analysis methods. It discusses the differences between quantitative and qualitative data/analysis, as well as various statistical and coding techniques used in each method. For quantitative analysis, it covers descriptive statistics, inferential statistics, univariate analysis including measures of central tendency and variation, bivariate analysis including crosstabulation and correlation, and multivariate analysis including elaboration models. For qualitative analysis, it discusses social anthropological versus interpretivist approaches, the relationship between data and ideas, strengths and weaknesses, and typical analysis steps including coding, data reduction, and conclusion drawing.
Qualitative research relies on textual data rather than numbers, focusing on accurate information. Quantitative research depends on objective numeric data suitable for statistics. It is important for media researchers to collect both qualitative and quantitative data to provide depth, cover a wide range of needed data effectively, and make results more reliable and understandable for audiences. Collecting both surveyed and textual information creates a more effective research project than only one type, as each provides different valuable insights.
Braun, Clarke & Hayfield Thematic Analysis Part 2Victoria Clarke
The second part of a four part lecture providing an introduction to thematic analysis and specifically the reflexive approach outlined by Braun and Clarke.
Business Research Method - Unit IV, AKTU, Lucknow SyllabusKartikeya Singh
The document summarizes various sampling methods and concepts related to determining sample size. It discusses probability sampling methods like simple random sampling, systematic sampling, stratified sampling, cluster sampling, and multistage sampling. It also discusses non-probability sampling methods such as convenience sampling, quota sampling, and judgmental sampling. The document provides details on each method and highlights key considerations for determining sample size such as the nature of the population, required accuracy and confidence level, and budget constraints.
Step Up Your Survey Research - Dawn of the Data Age Lecture SeriesLuciano Pesci, PhD
Most surveys are terrible. From poorly designed questions, to incoherent survey flow, to useless results, it’s no wonder data-driven organizations have so little faith in survey research. But this isn’t the fault of the tool, it’s because most surveys are built without adhering to some basic best practices, which once fixed can transform any survey from a zero to a hero. This lecture will show you how to create data-science quality surveys that provide unique and immediately actionable insight about your customers, competitors, and marketplace.
This Lecture Will:
-EXPLAIN THE DATA SCIENCE APPROACH TO SURVEY LAYOUT AND QUESTION DESIGN.
-HOW TO INCREASE RESPONSE AND COMPLETION RATES THROUGH ITERATIVE TESTING.
-LINKING SURVEY RESULTS TO OTHER DATA SOURCES TO ENRICH YOUR ANALYSIS.
You can watch this lecture here: https://youtu.be/WuBenXuVzqc
This document provides an overview of survey research, including survey design, objectives, advantages, disadvantages, and methods of data collection. It discusses determining the information required and target respondents for a survey. Common data collection methods described are personal interviews, telephone interviews, mail surveys, and online surveys. Key factors in choosing a method include the target population, accessibility, and costs. Both structured and unstructured interview techniques are covered.
Presentation on research methodologiesBilal Naqeeb
The document provides an overview of research methodologies. It defines research as an organized and systematic way of finding answers to questions. It notes that research is systematic because there are definite procedures and steps followed, and organized because there is a planned structure. The main purpose of research is to find answers to questions. The document then discusses different types of research such as primary and secondary research, as well as pure, applied, scientific and social research. It also outlines tools and techniques used for data collection in research such as surveys, experiments, interviews and case studies. Finally, it discusses key research concepts like variables, hypotheses, sampling, questionnaires and how to design good questions.
Braun, Clarke & Hayfield Thematic Analysis Part 4Victoria Clarke
The forth and final part of a four part lecture providing an introduction to thematic analysis and particularly the reflexive approach outlined by Braun & Clarke.
This document provides an overview of quantitative data analysis techniques used in sociology. It defines key terms like univariate analysis, bivariate analysis, and multivariate analysis. Univariate analysis examines one variable at a time through measures like frequency distributions, averages, and standard deviation. Bivariate analysis examines the relationship between two variables using cross-tabulation tables. Multivariate analysis examines relationships between multiple variables simultaneously. The document also discusses data coding, codebook construction, and ethical considerations in quantitative data analysis.
The document discusses the Likert scale, which is a technique used to measure opinions, attitudes, and other concepts by assigning numbers to varying degrees of agreement with statements. It involves developing statements, testing them, scoring responses, and selecting the statements that best discriminate between high and low scores. Likert scales are reliable, frequently used, allow for empirical testing, and are easier to construct than other scales. However, they only indicate whether respondents are more or less favorable rather than how much more or less favorable.
This document discusses key criteria for evaluating social research: validity, reliability, causality, and replication. It defines each concept and provides examples. Validity ensures research measures what it intends to measure through constructs like internal, external, and ecological validity. Reliability ensures consistency in measures over time and between observers. Causality looks for precedence between variables and correlation not due to other factors. Replication requires explicitly detailing procedures to allow others to reproduce results and ensure objectivity. The document provides an overview of important standards for high-quality social scientific research.
This document provides guidance on writing a research proposal. It discusses what constitutes research and outlines the typical structure and components of a research proposal, including an introduction with the problem statement and objectives, a literature review, research questions or hypotheses, research design and methodology, data collection and analysis plans, and a timeline. It also covers defining the population and sampling, developing and validating instruments, and formatting references. The goal is to present the key elements in a research proposal to systematically plan and design a research study.
The presentation covered key steps in analyzing survey data including defining goals, designing valid and reliable survey questions, collecting data, cleaning data, conducting descriptive statistics and correlations, comparing mean differences between groups, and clearly presenting results along with conclusions and recommendations. Piloting surveys and continuously improving methods was also emphasized.
Regardless of which strategies used by researcher to present their qualitative data, the presentation will result in identifying and acknowledging the multiple perspectives of the participants and researcher and the readers may then consider all perspectives in their interpretation of the research. This Slideshare provides information, strategies and references on how qualitative data could be presented.
The document discusses the process of data preparation, which involves validating raw data collected through surveys or observations to ensure it is accurate and unbiased. The key steps in data preparation are data validation, editing and coding, data entry, and data tabulation. Data validation aims to detect any fraud, screening errors, issues with data collection procedures, or incomplete responses. Descriptive statistics such as measures of central tendency (mean, median, mode) and variability (range, variance, standard deviation) are then used to analyze the prepared data. Graphs are also employed to visually depict patterns in the data.
This document discusses various sampling methods used in business research. It covers probability sampling techniques like simple random sampling, systematic sampling, stratified sampling, cluster sampling, and multistage sampling. It also discusses non-probability sampling techniques such as convenience sampling, quota sampling, and judgmental sampling. The key factors in determining sample size are described as the nature of the population, desired level of accuracy, available resources, and characteristics of the sampling method. Methods to reduce sampling errors like measurement, consistency checks, and quality control are also summarized.
Having systematic questionnaire design and testing procedures in place is vital for data quality,
particularly for a minimisation of the measurement error.
The document discusses the importance of rigor and robustness in research. It aims to provide insight into the meaning of rigor and how it can be maintained throughout the different stages of the research process, regardless of the research approach or paradigm used. Specifically, it discusses strategies for achieving rigor in areas like sampling techniques, data collection, data analysis, and reporting findings. Maintaining rigor is important for producing robust and reliable research results.
The document provides an overview of key aspects of survey design, including question styles, response formats, sampling, and implementation. It discusses developing a questionnaire, types of questions, optimizing question wording and structure, pre-testing surveys, and sampling techniques. The goal is to introduce rigorous methodology to plan, develop, and implement effective research questionnaires.
This document provides an overview of key concepts in descriptive statistics and intelligence testing including:
1. It describes four scales of measurement: nominal, ordinal, ratio, and equal-interval. It also discusses distributions, measures of central tendency, and measures of dispersion.
2. It discusses norms-referenced and criterion-referenced assessment. It also covers reliability, validity, and factors that can affect accurate assessment such as accommodations for students with disabilities.
3. It provides an overview of intelligence tests and behaviors they sample. It notes the dilemmas in assessing intelligence and describes some commonly used individual intelligence tests.
This document discusses various topics related to data analysis and hypothesis testing in business research methods. It covers data processing operations like editing, coding, classification and tabulation. It also discusses various graphical representations of data like bar charts, pie charts, histograms and their appropriate usage. The document then explains the concepts of hypothesis, null hypothesis and alternative hypothesis. It describes hypothesis testing logic and the concepts of type 1 and type 2 errors. It lists the steps involved in hypothesis testing like setting up the hypothesis, determining test statistics, critical regions, and making decisions.
The document provides an overview of quantitative and qualitative data analysis methods. It discusses the differences between quantitative and qualitative data/analysis, as well as various statistical and coding techniques used in each method. For quantitative analysis, it covers descriptive statistics, inferential statistics, univariate analysis including measures of central tendency and variation, bivariate analysis including crosstabulation and correlation, and multivariate analysis including elaboration models. For qualitative analysis, it discusses social anthropological versus interpretivist approaches, the relationship between data and ideas, strengths and weaknesses, and typical analysis steps including coding, data reduction, and conclusion drawing.
Qualitative research relies on textual data rather than numbers, focusing on accurate information. Quantitative research depends on objective numeric data suitable for statistics. It is important for media researchers to collect both qualitative and quantitative data to provide depth, cover a wide range of needed data effectively, and make results more reliable and understandable for audiences. Collecting both surveyed and textual information creates a more effective research project than only one type, as each provides different valuable insights.
Braun, Clarke & Hayfield Thematic Analysis Part 2Victoria Clarke
The second part of a four part lecture providing an introduction to thematic analysis and specifically the reflexive approach outlined by Braun and Clarke.
Business Research Method - Unit IV, AKTU, Lucknow SyllabusKartikeya Singh
The document summarizes various sampling methods and concepts related to determining sample size. It discusses probability sampling methods like simple random sampling, systematic sampling, stratified sampling, cluster sampling, and multistage sampling. It also discusses non-probability sampling methods such as convenience sampling, quota sampling, and judgmental sampling. The document provides details on each method and highlights key considerations for determining sample size such as the nature of the population, required accuracy and confidence level, and budget constraints.
Step Up Your Survey Research - Dawn of the Data Age Lecture SeriesLuciano Pesci, PhD
Most surveys are terrible. From poorly designed questions, to incoherent survey flow, to useless results, it’s no wonder data-driven organizations have so little faith in survey research. But this isn’t the fault of the tool, it’s because most surveys are built without adhering to some basic best practices, which once fixed can transform any survey from a zero to a hero. This lecture will show you how to create data-science quality surveys that provide unique and immediately actionable insight about your customers, competitors, and marketplace.
This Lecture Will:
-EXPLAIN THE DATA SCIENCE APPROACH TO SURVEY LAYOUT AND QUESTION DESIGN.
-HOW TO INCREASE RESPONSE AND COMPLETION RATES THROUGH ITERATIVE TESTING.
-LINKING SURVEY RESULTS TO OTHER DATA SOURCES TO ENRICH YOUR ANALYSIS.
You can watch this lecture here: https://youtu.be/WuBenXuVzqc
This document provides an overview of survey research, including survey design, objectives, advantages, disadvantages, and methods of data collection. It discusses determining the information required and target respondents for a survey. Common data collection methods described are personal interviews, telephone interviews, mail surveys, and online surveys. Key factors in choosing a method include the target population, accessibility, and costs. Both structured and unstructured interview techniques are covered.
Presentation on research methodologiesBilal Naqeeb
The document provides an overview of research methodologies. It defines research as an organized and systematic way of finding answers to questions. It notes that research is systematic because there are definite procedures and steps followed, and organized because there is a planned structure. The main purpose of research is to find answers to questions. The document then discusses different types of research such as primary and secondary research, as well as pure, applied, scientific and social research. It also outlines tools and techniques used for data collection in research such as surveys, experiments, interviews and case studies. Finally, it discusses key research concepts like variables, hypotheses, sampling, questionnaires and how to design good questions.
Braun, Clarke & Hayfield Thematic Analysis Part 4Victoria Clarke
The forth and final part of a four part lecture providing an introduction to thematic analysis and particularly the reflexive approach outlined by Braun & Clarke.
This document provides an overview of quantitative data analysis techniques used in sociology. It defines key terms like univariate analysis, bivariate analysis, and multivariate analysis. Univariate analysis examines one variable at a time through measures like frequency distributions, averages, and standard deviation. Bivariate analysis examines the relationship between two variables using cross-tabulation tables. Multivariate analysis examines relationships between multiple variables simultaneously. The document also discusses data coding, codebook construction, and ethical considerations in quantitative data analysis.
The document discusses the Likert scale, which is a technique used to measure opinions, attitudes, and other concepts by assigning numbers to varying degrees of agreement with statements. It involves developing statements, testing them, scoring responses, and selecting the statements that best discriminate between high and low scores. Likert scales are reliable, frequently used, allow for empirical testing, and are easier to construct than other scales. However, they only indicate whether respondents are more or less favorable rather than how much more or less favorable.
This document discusses key criteria for evaluating social research: validity, reliability, causality, and replication. It defines each concept and provides examples. Validity ensures research measures what it intends to measure through constructs like internal, external, and ecological validity. Reliability ensures consistency in measures over time and between observers. Causality looks for precedence between variables and correlation not due to other factors. Replication requires explicitly detailing procedures to allow others to reproduce results and ensure objectivity. The document provides an overview of important standards for high-quality social scientific research.
This document provides guidance on writing a research proposal. It discusses what constitutes research and outlines the typical structure and components of a research proposal, including an introduction with the problem statement and objectives, a literature review, research questions or hypotheses, research design and methodology, data collection and analysis plans, and a timeline. It also covers defining the population and sampling, developing and validating instruments, and formatting references. The goal is to present the key elements in a research proposal to systematically plan and design a research study.
Quantitative research designs establish relationships between independent and dependent variables. There are three main types of quantitative research designs: experimental, quasi-experimental, and non-experimental (which includes cross-sectional, longitudinal, and survey designs). Experimental designs deliberately introduce a treatment to observe results, while quasi-experimental designs lack random assignment. Non-experimental designs observe relationships without manipulation.
This document outlines the key aspects of research including: defining research as a systematic process of investigating a problem through collecting data to answer a question; describing the main types of research such as fundamental, quantitative, applied, and qualitative; and explaining the common steps of research such as formulating the problem, developing hypotheses, collecting and analyzing data, and reporting results. The overall goal of research is to increase knowledge and understanding of a topic.
HI6008 Business Research Lecture 01(1) (1).pptxabeerarif
Assignment 3 Reflective writing aims to get you to think
about your learning and understand your learning experiences.Evaluate the effectiveness and your usefulness of the learning experience
Make judgements that are clearly connected to observations you have made.
Answer the questions:
− What is your opinion about learning experience?
− What is the value of this experience?
2. Explain how this learning process will be useful to you
Consider: In what ways might this learning experience serve you in:course
− program
− future career
− life generally
Answer the question: ‘How you will transfer or apply your new knowledge and
insights in the future?’
3. Describe objectively what happened in the learning process
Give the details of what happened in the learning process. Answer the question:
‘What you did, read, see, and hear?
4. Evaluate what you learn
Make judgments connected to observations you have made in the Business
Research. Answer the question: ‘How Business Research was useful for your
Research Learning Process?’
5. Explain your learning process:
This document provides an overview of business research methods. It discusses why business research is important for engineers and defines what research is, including that it is a systematic search for truth and new knowledge. It outlines the scientific method process and types of research such as descriptive vs analytical, applied vs fundamental, quantitative vs qualitative, and conceptual vs empirical. COVID-19 statistics are also presented along with the current vaccine status.
Here are a few ways we could use content analysis to test that belief:
1. Select a random sample of news articles, TV shows, movies, etc. that portray poor people. Develop a coding scheme to categorize how the poor are portrayed - e.g. as lazy, criminal, dependent on welfare, hard-working but struggling, etc. Two researchers would code the same materials to check reliability.
2. Count the frequency of different portrayals to see which are most common. We could test if negative portrayals outnumber positive or neutral ones in a statistically significant way.
3. Code for socioeconomic or racial demographics of characters portrayed as poor. We could test if certain groups are disproportionately represented in
The document provides an overview of key concepts in research methodology. It discusses definitions of research, objectives of research such as gaining new insights or testing hypotheses. It covers research design principles like defining variables and controlling for extraneous factors. It also outlines different research designs for exploratory, descriptive and experimental studies. Sample design concepts involving probability and non-probability sampling are presented. Methods of primary data collection like observation, interviews and questionnaires are explained. Finally, it provides guidance on constructing questionnaires and successful interviewing techniques.
This document provides an introduction and overview of research methodology. It discusses that research is both a set of skills and a way of thinking that involves questioning observations, exploring further, understanding explanations, and drawing conclusions. Research is defined as an inquisitive, critical, and analytical observation of work or practice to gain in-depth knowledge. The document also outlines different types of research such as descriptive vs analytical, applied vs fundamental, quantitative vs qualitative vs mixed methods, and conceptual vs empirical. It emphasizes that research methodology considers the logic and rationale behind the methods used in a research study.
This document discusses research paradigms and provides examples of different types of research paradigms. It begins by defining what a research paradigm is - the underlying beliefs, assumptions, and methodologies that guide research. It then outlines four main research paradigms: positivism/quantitative, interpretivist/qualitative, critical, and pragmatic. For each paradigm, it describes the ontology (view of reality), epistemology (relationship between the researcher and what is being researched), and methodology. It provides examples of research questions and studies for each paradigm. The document discusses the strengths and limitations of different paradigms and whether they meet the needs of practicing educators.
This document discusses research paradigms in online and distance education research. It begins by defining key terms like research paradigm, ontology, epistemology and methodology. It then outlines four main research paradigms: positivism, interpretivism, critical theory, and pragmatism. For each paradigm, it describes the underlying beliefs about the nature of knowledge and reality, as well as typical research questions and methodologies. Examples of studies using different paradigms are also provided. The document concludes by discussing considerations for choosing a research paradigm and what makes a good research question.
Research 101: Scientific Research DesignsHarold Gamero
This document discusses research design and various options. It defines a research design as a comprehensive plan for collecting empirical data that specifies processes for data collection, instrument development, and sampling. There are two main approaches: interpretive methods aimed at constructing theories from observed data (e.g. ethnography) and positivist methods aimed at testing theories and hypotheses (e.g. experiments). Key attributes of research designs discussed are internal validity, external validity, construct validity, and validity of statistical conclusions. Popular research design options summarized are experiments, surveys, secondary data analysis, case studies, focus groups, action research, and ethnography. The document emphasizes selecting a design based on the nature of the phenomenon being studied and collecting both qualitative and quantitative
Research Design in Business Research ManagementKoushik438334
This document discusses various research design concepts including exploratory, descriptive, and causal research designs. It defines key terms like independent and dependent variables, extraneous variables, control and control groups, treatments, hypotheses, experimental and non-experimental designs, cross-sectional and longitudinal designs. It compares exploratory, descriptive, and causal research and discusses their objectives, characteristics, and methods. It also discusses uses of different research designs and how to select appropriate designs based on research objectives.
This document provides an overview of business research methods. It discusses the role and scope of business research, including how it aids decision making. It defines basic and applied research and gives examples. The document also outlines the research process, including defining problems, designing the research, sampling, data collection, analysis, and reporting. Additionally, it covers developing and verifying theories, and distinguishes between research projects and programs.
This document provides an overview of research methodology and key concepts in research. It discusses that research aims to discover unknown knowledge through systematic investigation. The main objectives of research are exploration, description, diagnosis, and hypothesis testing. Business research examines all areas of a business to maximize profits. Research can be qualitative or quantitative. Key types include descriptive, analytical, applied, fundamental, causal, and exploratory. Research questions define the problem to be examined, while objectives and hypotheses make testable claims. Theories guide research by informing questions and interpretations.
The document provides an overview of research design, including:
1. Research design involves planning how a study will be conducted to answer research questions and control variance. It specifies data sources, approaches, and time/cost budgets.
2. Key concepts in research design include independent and dependent variables, control of extraneous variables, and experimental and control groups.
3. There are different types of research design including exploratory, causal, descriptive, and experimental designs. Experimental designs further include pre-experimental, true experimental, and quasi-experimental approaches.
The document discusses research design, which is the plan or blueprint for how a research study will be conducted. It involves determining what questions the research aims to answer, what type of data is needed, where to find that data, and how to analyze results. The key aspects of research design discussed include variables, hypotheses, experimental and control groups, and treatments. Different types of research design are also outlined, such as exploratory, causal, descriptive, and experimental designs. Experimental design specifically aims to determine cause-and-effect relationships between variables.
The document provides an overview of research design, including:
1. Research design involves planning how a study will be conducted to answer research questions and control variance. It specifies data sources, approaches, and time/cost budgets.
2. Key concepts in research design include independent and dependent variables, control of extraneous variables, and experimental and control groups.
3. Common types of research design are exploratory, causal, descriptive, and experimental designs. Experimental designs manipulate independent variables to measure their effects on dependent variables.
Explanatory, Descriptive and Exploratory Research.pptxDulaSanbato1
Research can be classified in different ways such as by purpose, process, and outcomes. There are several types of research including exploratory research, descriptive research, and explanatory research. Exploratory research is conducted when little is known about a topic and aims to gain insights rather than test hypotheses. Descriptive research describes characteristics of a topic as it exists currently. Explanatory research builds on exploratory and descriptive research to understand phenomena by discovering causal relationships between variables and answering "why" questions. The goals, strengths, and weaknesses of each type of research are outlined.
This document outlines steps for evaluating a strategic public relations and advertising plan. It discusses evaluating awareness, acceptance, and action objectives using various metrics like media coverage, surveys, requests for information, and results. Evaluation should occur at three stages: implementation reports, progress reports, and final reports. Both quantitative and qualitative research methods can be used, including surveys, content analysis, and interviews. The ultimate goal of evaluation is to determine the value and impact public relations brought to the overall organization.
The document outlines the components of a public relations campaign plan, including an executive summary, situation analysis, strategy and tactic recommendations, timeline, budget, and evaluation plan. It recommends including specific publics, goals, and objectives for each tactic, as well as the budget and evaluation methods. Sample sections provide details on how to structure a timeline using a Gantt chart and PERT chart, and include categories for budgeting personnel, materials, media costs, equipment, and administrative expenses.
This document discusses selecting communication tactics for public relations and advertising campaigns. It begins by defining communication tactics as the visible elements of a strategic plan, such as websites, news releases, and events. When selecting tactics, the goals, objectives, organization, and public tastes should be considered. It then provides examples of different types of conventional, internal/external, mass/target, print/electronic, and strategic communication tactics that could be used.
The document discusses developing an effective message strategy. It covers selecting the appropriate communication model, using rhetorical devices to craft persuasive messages, and elements of verbal and non-verbal communication. Key aspects of developing messages include using ethical and legal language, crafting clear and salient content, employing symbols and branding to create a consistent organizational message.
1. The document discusses various nonparametric statistical tests including the Wilcoxon Rank Sum Test, Sign Test, Kruskal-Wallis Test, and Friedman test that can be used when the assumptions of parametric tests are violated.
2. It provides examples of applying each test using SPSS and interpreting the results, such as comparing two painkillers using the Wilcoxon Rank Sum Test and comparing commute times with and without flextime using the Wilcoxon Signed Rank Sum Test.
3. The Friedman Test is introduced for comparing ordinal data from a randomized block experiment, and an example compares applicant ratings across multiple managers to test for differences between the managers.
This document discusses quantitative research methods for model building and multiple regression analysis. It covers regression diagnostics, polynomial models, nominal variables in regression, stepwise regression, and statistical analyses for different variable types. It also provides an overview of simple linear regression, multiple regression, and logistic regression models. Examples are given to demonstrate how to estimate regression coefficients, assess model fit, interpret results, and check assumptions using SPSS.
This document discusses quantitative research methods including correlation, simple linear regression, and multiple regression. It provides examples of how to conduct simple linear regression using SPSS to analyze the relationship between two variables and predict the dependent variable based on the independent variable. It then expands the discussion to multiple linear regression, using SPSS to analyze the relationships between multiple independent variables and one dependent variable. Key steps of assessing the model such as the coefficient of determination and F-test of ANOVA are also covered.
This document discusses quantitative research methods and analysis of variance (ANOVA). It covers one-way ANOVA, which allows comparison of three or more groups, and examples comparing differences between age groups and types of bumpers. Requirements for ANOVA like normality and independence are addressed. Post-hoc tests for identifying specific group differences are also introduced.
This document discusses quantitative research methods and statistical inference. It covers topics like probability distributions, sampling distributions, estimation, hypothesis testing, and different statistical tests. Key points include:
- Probability distributions describe random variables and their associated probabilities. The normal distribution is important and described by its mean and standard deviation.
- Sampling distributions allow making inferences about populations based on samples. The sampling distribution of the mean approximates a normal distribution as the sample size increases.
- Statistical inference involves estimation and hypothesis testing. Estimation provides a value for an unknown population parameter based on a sample statistic. Hypothesis testing compares a null hypothesis to an alternative hypothesis based on a test statistic and can result in type 1 or type 2 errors.
This document discusses the elements and principles of design. It defines the seven elements of design as line, shape, negative space, volume, value, color, and texture. It provides details on line as the most basic element, describing how lines can be used in preliminary sketches, how they can imply emotions, and how vertical, horizontal, and diagonal lines have different effects. The principles of design will be covered in the next topic.
This document provides an overview of wound healing, its functions, stages, mechanisms, factors affecting it, and complications.
A wound is a break in the integrity of the skin or tissues, which may be associated with disruption of the structure and function.
Healing is the body’s response to injury in an attempt to restore normal structure and functions.
Healing can occur in two ways: Regeneration and Repair
There are 4 phases of wound healing: hemostasis, inflammation, proliferation, and remodeling. This document also describes the mechanism of wound healing. Factors that affect healing include infection, uncontrolled diabetes, poor nutrition, age, anemia, the presence of foreign bodies, etc.
Complications of wound healing like infection, hyperpigmentation of scar, contractures, and keloid formation.
Level 3 NCEA - NZ: A Nation In the Making 1872 - 1900 SML.pptHenry Hollis
The History of NZ 1870-1900.
Making of a Nation.
From the NZ Wars to Liberals,
Richard Seddon, George Grey,
Social Laboratory, New Zealand,
Confiscations, Kotahitanga, Kingitanga, Parliament, Suffrage, Repudiation, Economic Change, Agriculture, Gold Mining, Timber, Flax, Sheep, Dairying,
This presentation was provided by Rebecca Benner, Ph.D., of the American Society of Anesthesiologists, for the second session of NISO's 2024 Training Series "DEIA in the Scholarly Landscape." Session Two: 'Expanding Pathways to Publishing Careers,' was held June 13, 2024.
Walmart Business+ and Spark Good for Nonprofits.pdfTechSoup
"Learn about all the ways Walmart supports nonprofit organizations.
You will hear from Liz Willett, the Head of Nonprofits, and hear about what Walmart is doing to help nonprofits, including Walmart Business and Spark Good. Walmart Business+ is a new offer for nonprofits that offers discounts and also streamlines nonprofits order and expense tracking, saving time and money.
The webinar may also give some examples on how nonprofits can best leverage Walmart Business+.
The event will cover the following::
Walmart Business + (https://business.walmart.com/plus) is a new shopping experience for nonprofits, schools, and local business customers that connects an exclusive online shopping experience to stores. Benefits include free delivery and shipping, a 'Spend Analytics” feature, special discounts, deals and tax-exempt shopping.
Special TechSoup offer for a free 180 days membership, and up to $150 in discounts on eligible orders.
Spark Good (walmart.com/sparkgood) is a charitable platform that enables nonprofits to receive donations directly from customers and associates.
Answers about how you can do more with Walmart!"
How to Make a Field Mandatory in Odoo 17Celine George
In Odoo, making a field required can be done through both Python code and XML views. When you set the required attribute to True in Python code, it makes the field required across all views where it's used. Conversely, when you set the required attribute in XML views, it makes the field required only in the context of that particular view.
Chapter wise All Notes of First year Basic Civil Engineering.pptxDenish Jangid
Chapter wise All Notes of First year Basic Civil Engineering
Syllabus
Chapter-1
Introduction to objective, scope and outcome the subject
Chapter 2
Introduction: Scope and Specialization of Civil Engineering, Role of civil Engineer in Society, Impact of infrastructural development on economy of country.
Chapter 3
Surveying: Object Principles & Types of Surveying; Site Plans, Plans & Maps; Scales & Unit of different Measurements.
Linear Measurements: Instruments used. Linear Measurement by Tape, Ranging out Survey Lines and overcoming Obstructions; Measurements on sloping ground; Tape corrections, conventional symbols. Angular Measurements: Instruments used; Introduction to Compass Surveying, Bearings and Longitude & Latitude of a Line, Introduction to total station.
Levelling: Instrument used Object of levelling, Methods of levelling in brief, and Contour maps.
Chapter 4
Buildings: Selection of site for Buildings, Layout of Building Plan, Types of buildings, Plinth area, carpet area, floor space index, Introduction to building byelaws, concept of sun light & ventilation. Components of Buildings & their functions, Basic concept of R.C.C., Introduction to types of foundation
Chapter 5
Transportation: Introduction to Transportation Engineering; Traffic and Road Safety: Types and Characteristics of Various Modes of Transportation; Various Road Traffic Signs, Causes of Accidents and Road Safety Measures.
Chapter 6
Environmental Engineering: Environmental Pollution, Environmental Acts and Regulations, Functional Concepts of Ecology, Basics of Species, Biodiversity, Ecosystem, Hydrological Cycle; Chemical Cycles: Carbon, Nitrogen & Phosphorus; Energy Flow in Ecosystems.
Water Pollution: Water Quality standards, Introduction to Treatment & Disposal of Waste Water. Reuse and Saving of Water, Rain Water Harvesting. Solid Waste Management: Classification of Solid Waste, Collection, Transportation and Disposal of Solid. Recycling of Solid Waste: Energy Recovery, Sanitary Landfill, On-Site Sanitation. Air & Noise Pollution: Primary and Secondary air pollutants, Harmful effects of Air Pollution, Control of Air Pollution. . Noise Pollution Harmful Effects of noise pollution, control of noise pollution, Global warming & Climate Change, Ozone depletion, Greenhouse effect
Text Books:
1. Palancharmy, Basic Civil Engineering, McGraw Hill publishers.
2. Satheesh Gopi, Basic Civil Engineering, Pearson Publishers.
3. Ketki Rangwala Dalal, Essentials of Civil Engineering, Charotar Publishing House.
4. BCP, Surveying volume 1
The chapter Lifelines of National Economy in Class 10 Geography focuses on the various modes of transportation and communication that play a vital role in the economic development of a country. These lifelines are crucial for the movement of goods, services, and people, thereby connecting different regions and promoting economic activities.
How to Setup Warehouse & Location in Odoo 17 InventoryCeline George
In this slide, we'll explore how to set up warehouses and locations in Odoo 17 Inventory. This will help us manage our stock effectively, track inventory levels, and streamline warehouse operations.
Gender and Mental Health - Counselling and Family Therapy Applications and In...PsychoTech Services
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1. Quantitative Research Methods
Lecture 1
1.What is scientific research? What is quantitative research?
2.Why we need research?
3.Who is conducting the research?
4.What is the research process?
5.What is the language of research?
2. 1.What is scientific research? What is
quantitative research?
• Methods of knowing:
▫ by tenacity (“something is true
because it has always been true”);
▫ by intuition (“something is true
because it’s self-evident and stands to
reason”);
▫ by authority (“something is true
because a trusted source says so”);
▫ by scientific research (“something is
true because research results tell so”).
3. 1.What is scientific research? What is
quantitative research?
• Characteristics of Scientific Research (Wimmer
& Dominick, 1997, pp. 9-11):
▫ public (vs. private)
▫ objective (vs. subjective)
▫ empirical (vs. speculative)
▫ systematic and cumulative (vs. ad-hoc and
discontinued)
▫ predictive (vs. time/space-bound)
4. 2.Why do we the scientific research?
• Purposes of Scientific Research: to
discover/generate general laws underlying a
social process (i.e., theory) that help to
▫ describe the current state or past trend of the
process
▫ explain the causes of the process
▫ predict the future trajectory of the process
▫ control (i.e., intervene) the direction, pace, and
outcome of the process
5. A research for this class…
• Pre-course survey
• Q: what decisions can I make from the this data?
6. 3.Who is conducting the research?
• Decision makers in industry and academic
initiated the research
• In industry:
▫ Internally: a research expert within the
organization
▫ Externally: a research company
Arab Media Outlook was conducted by Deloitte
Nielson: market research company “what people
watch, what people buy”
• In academic: a professor
9. 4.What is the research process?
4.1 Pre-research
4.2 Research
4.3 Post-research
10. 4.1. Pre-research Phase
• Identifying a need for research
• Research questions guide the research
• Research hypotheses
• Deciding on the appropriate Research Methods
11. Research Methods
• Quantitative or Qualitative?
▫ Survey
▫ Content analysis
▫ Experiment
▫ Interview
▫ Focus group
▫ Observation
▫ Case study
▫ ……
12. Basic Types of Qualitative Methods
Focus group Interview Observation
13. Basic Types of Quantitative Methods
Survey Experiment Content analysis
14. What is Survey?
• Survey is a research technique that uses a
standardized questionnaire to collect
information about attitudes, opinions,
behaviors, and background and lifestyle
characteristics from a sample of respondents.
15. What Is Experiment?
Experiment is a procedure in which subjects are
first randomly assigned to experimental and
control conditions, with those under
experimental condition(s) given exposure to
certain stimulus or treatment whereas those
under control condition given no exposure, in
order to assess the effects of the message.
16. Example
A research on public policy:
Framing, Psychological Distance, &
Audience Perception An experiment on
perception of the BRI by Chinese and UAE
students (Shujun Jiang et al, 2018)
17. 2.9
4.12
4.15
3.79
3.22
3.24
4.36
4.29
3.95
3.33
3.85
2.48
3.3
3.34
3.19
3.01
3.31
4.09
3.94
3.71
3.58
3.91
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5
I understand China's the Belt and Road Initiative
B1 The Belt and Road Initiative will benefit my country.
B2 The Belt and Road Initiative will benefit COUNTRIES along the route.
B3 The Belt and Road Initiative will benefit INDIVIDUALS in the countries along
route.
B4 The Belt and Road Initiative will benefit me.
B5 UAE plays an important strategic role in China’s the Belt and Road Initiative
A1 The Belt and Road Initiative will benefit my country.
A2 The Belt and Road Initiative will benefit COUTRIES along the route.
A3 The Belt and Road Initiative will benefit INDIVIDUALS in the countries along
route.
A4 The Belt and Road Initiative will benefit me.
A5 UAE plays an important strategic role in China’s the Belt and Road Initiative
Perception of BRI
China UAE
18. Hypothesis testing
Before
Chin
a
Individual
Frame
ANOVA
No
differenceSocietal Frame
Control
UAE Individual
Frame
ANOVA
No
differenceSocietal Frame
Control
After
China Individual
Frame
T-test Sig.
Individual >
Societal
A3
Societal Frame
UAE Individual
Frame
T-test
No difference
Societal Frame
After
Societal
Frame
China T-test
No differenceUAE
Individual
Frame
China T-test Sig.
China > UAE
A2
A3UAE
Hypothesis was partially supported
For individual new frames, socially proximal entity (China) > socially distant
entity (UAE)
19. What is Content Analysis?
• Content analysis is a research method for the
studying and analyzing communication content
in a systematic, objective, and quantitative
manner for the purpose of measuring variables.
• In content analysis, communication content is
examined independently of those who produced
it. Communication professionals are not queried
about their attituds, opinions, and motivations
in the production of the content.
20. Example
• A research on News Produsers:
• Factors Influencing User Engagement in
Instagram News Produsers’ Accounts: A Case
in the UAE (Mansour Alameri & Shujun Jiang,
2018)
23. Post with soft news are more attracted to comments than posts with hard news.
24. 4.2. Research Phase
• In industry:
▫ Research expert meets executives to learn
research question, research methods, relevant
population, timetable, budget
▫ Then, literature review—measurement—train data
collectors—collect data– data analysis—report
• In academic
▫ Professors do all the above and write a paper for
conference or academic journal publication
25. 4.3. Post-research phase
• Executives evaluate the research results and
make decision
• Professors evaluate the results and limitations to
improve future studies.
26. 5.What is the language of research?
• 5.1. Theory
▫ “Theory is a set of related propositions that presents a
systematic view of phenomena by specifying
relationships among concepts.” (Winner and
Dominick, 1997, p. 11)
▫ Theory aims to explain the causes and predict the
consequences of a process as general as possible (i.e.,
as time-less and space-less as possible).
27. 5.2 What Is Concept?
• A concept is the smallest element in a theory, as
bricks in a building;
• A concept is the abstract representation of a
phenomenon under investigation;
• Some authors call a broad concept as “construct”
that entails a number of narrow concepts; however,
the difference between construct and concept is
always relative because a construct may be the
constituent concept of another construct whereas a
concept may contain other concepts.
28. 5.3 What Is Relationship?
• A relationship is a specification of the structural
connection between or among concepts in a
theory;
• The specification of a relationship includes:
▫ the nature (correlational or causal) of the relationship;
▫ the form (linear or otherwise) of the relationship;
▫ the direction (positive or negative) of the relationship;
▫ the strength (strong or modest) of the relationship.
29. Examples of Relationship
• Need for the Internet: dissatisfaction with the
conventional media and expected satisfaction with the
Internet drives adoption and use of the Internet
30. 5.4 What Is Proposition?
• A formal presentation of the nature, form,
direction, and strength of a relationship
between/among theoretical concepts, which
could and should be in all three formats:
▫ Verbal description
▫ Graphic illustration
▫ Mathematical specification
31. Example of a Proposition
• Knowledge gap increases over time as the
different segments of a society learn new
information at a differential rate.
High SES Group
Low SES Group
Time
Knowledge
(Kh-Kl)=a+bTime
32. 5.5 Terms Related to Theory
Narrowly Used Broadly Used
Hypothesis
a tentative theory
without fully tested
a theory at a early
stage
Model
a mathematical
version of a theory
a formally stated
theory
Framework
an analytic plan
based on a theory
a theory used for
empirical analysis
35. 5.7 What Is Conceptualization?
• A thought process to identify key concepts and
formulate their structural relationship, based on
existing theory and past research;
• Conceptualization is to translate concrete events
and/or phenomena to abstract symbols and
propositions, which will necessarily ignore rich
details of the reality.
36. Structural Relationship among
Theoretical Concepts
Outcome
(Dependent
Variable)
Cause (Independent
Variable)
Control/Confound
Variable
Mediator
(Intervening
Variable)
Direct Impact
Indirect Impact
Conditioner
(Moderator Variable)
37. 5.8 What Is Operationalization?
• A process to translate the abstract concepts into
concrete variables that can be quantitatively
measured by a questionnaire (in survey), coding
sheet (in content analysis), physiological
instruments (in experiment), and other means of
data collection;
• The quality of operationalization is evaluated by
▫ validity
▫ reliability
▫ practicality
39. Comparison among Concept,
Variable, and Measure
Concept Variable Measure
Consumption
Behavior
Having happy
meal
How many happy
meal did you eat last
month?
Shopping
Behavior
Online
Shopping
How often did you
shop online?
40. 5.9 What is Measurement?
• Measurement: is a set of rules for assigning
numbers, which represent values of varying
degrees of precision, for reported or observed
behaviors, attitudes, opinions, and other
individual, group, organization, content, or issue
characteristics.
• Measurement should be
Valid
Reliable
41. 5.9.1 What is Validity and Reliability?
• Validity addresses whether or not you have
asked the right question to get the answers that
represents the phenomenon you are
researching.
• Reliability addresses the issue of the consistency
of the question that measures the concept being
studied.
42. 5.9.1 What Is Validity & Reliability?
• Validity: the extent to which the results of a
study (i.e., the concepts and/or their
relationship) represent what the study is
intended to find.
• Reliability: the extent to which the results of a
study can be replicated among the same
population at a different time or among different
population(s) at any time.
43. 5.9.1 What is Validity & Reliability?
• Internal validity is concerned with whether the
measurement is an accurate representation of
the concept being studied.
E.g. internet use vs internet access
• External validity refers to whether the results of
a research study are generalizable to the
population of interest.
E.g. A study of college student vs population
44. 5.9.1 Validity vs. Reliability
Invalid & Unreliable Reliable but Invalid Valid & Reliable
45. 5.9.1 Evaluation of Validity and
Reliability
• Validity is a conceptual question that doesn’t
have any direct and conclusive way of testing.
• Reliability is an empirical question that can be
evaluated based on test-retest data.