Podcast
Questions and Answers
Which qualitative method is primarily focused on the in-depth study of a single instance or event?
Which qualitative method is primarily focused on the in-depth study of a single instance or event?
What is a key strength of qualitative methods?
What is a key strength of qualitative methods?
In quantitative methods, which statistical technique is used for hypothesis testing?
In quantitative methods, which statistical technique is used for hypothesis testing?
Which type of data analysis involves using summary statistics such as mean, median, and mode?
Which type of data analysis involves using summary statistics such as mean, median, and mode?
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What is a disadvantage of qualitative methods?
What is a disadvantage of qualitative methods?
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Which of the following is not a component of survey design?
Which of the following is not a component of survey design?
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Which method would you use to collect numerical data for quantitative research?
Which method would you use to collect numerical data for quantitative research?
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What is a potential issue to consider in survey design regarding participant responses?
What is a potential issue to consider in survey design regarding participant responses?
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Study Notes
Research Methodology
Qualitative Methods
- Focus on gaining in-depth understanding of social phenomena through non-numerical data
- Methods:
- Case studies
- Content analysis
- Ethnography
- Focus groups
- Interviews
- Observations
- Data collection:
- Text, images, videos, and audio recordings
- Field notes and memos
- Data analysis:
- Coding and theme identification
- Memoing and data display
- Pattern and theme identification
- Strengths:
- Rich, detailed insights into social phenomena
- Flexibility and adaptability
- Weaknesses:
- Limited generalizability
- Time-consuming and labor-intensive
Quantitative Methods
- Focus on numerical data and statistical analysis to test hypotheses
- Methods:
- Experiments
- Surveys
- Correlational studies
- Quasi-experiments
- Data collection:
- Numerical data from surveys, questionnaires, or experiments
- Data analysis:
- Descriptive statistics (mean, median, mode)
- Inferential statistics (t-tests, ANOVA, regression)
- Hypothesis testing
- Strengths:
- High generalizability
- Objectivity and precision
- Weaknesses:
- Limited depth of understanding
- Risk of oversimplification
Data Analysis
- Process of interpreting and making sense of data
- Types:
- Descriptive analysis (summary statistics)
- Inferential analysis (hypothesis testing)
- Exploratory analysis (pattern identification)
- Predictive analysis (modeling)
- Techniques:
- Data visualization
- Data mining
- Statistical modeling
- Machine learning
- Importance:
- Informs decision-making and policy development
- Identifies patterns and trends
- Tests hypotheses and theories
Survey Design
- Process of creating a survey to collect data from a sample of participants
- Types:
- Self-administered surveys (online, mail, or in-person)
- Interviewer-administered surveys (telephone, in-person, or video)
- Components:
- Questionnaire (questions and format)
- Sampling plan (participant selection and recruitment)
- Data collection plan (mode and timing)
- Considerations:
- Survey length and complexity
- Question wording and bias
- Response rates and non-response bias
- Data quality and reliability
Research Methodology
Qualitative Methods
- Gain in-depth understanding of social phenomena through non-numerical data using methods like case studies, content analysis, ethnography, focus groups, interviews, and observations
- Collect non-numerical data such as text, images, videos, and audio recordings, as well as field notes and memos
- Analyze data using coding and theme identification, memoing and data display, and pattern and theme identification
- Strengths: rich, detailed insights into social phenomena, flexibility, and adaptability
- Weaknesses: limited generalizability, time-consuming and labor-intensive
Quantitative Methods
- Focus on numerical data and statistical analysis to test hypotheses using experiments, surveys, correlational studies, and quasi-experiments
- Collect numerical data from surveys, questionnaires, or experiments
- Analyze data using descriptive statistics, inferential statistics, and hypothesis testing
- Strengths: high generalizability, objectivity, and precision
- Weaknesses: limited depth of understanding, risk of oversimplification
Data Analysis
- Interpret and make sense of data through descriptive analysis, inferential analysis, exploratory analysis, and predictive analysis
- Use techniques like data visualization, data mining, statistical modeling, and machine learning
- Importance: informs decision-making and policy development, identifies patterns and trends, and tests hypotheses and theories
Survey Design
- Create a survey to collect data from a sample of participants using self-administered or interviewer-administered surveys
- Components: questionnaire, sampling plan, and data collection plan
- Considerations: survey length and complexity, question wording and bias, response rates and non-response bias, and data quality and reliability
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Description
This quiz explores the world of qualitative research methods, including case studies, content analysis, ethnography, focus groups, interviews, and observations. It delves into data collection, data analysis, and the strengths of qualitative methods.
