Data Collection and Measurement Levels

Recap: Data Collection and Levels of Measurement

• Data collection is an important step in research.
• There are four levels of measurement for data: nominal, ordinal, interval, and ratio.
• Nominal scales describe categories and are often used for classifying data.
• Ordinal scales allow data to be ranked in order, but intervals are unknown.
• Interval scales are based on scales where the distance between them is equal and meaningful.
• Ratio scales are the most meaningful, having an absolute true zero point.

Data Analysis - Quantitative

• Quantitative data analysis involves analyzing numbers or figures.
• There are two broad types of quantitative data analysis: descriptive and inferential.
• Descriptive statistics describe or summarise sample data.
• Inferential statistics attempt to generalize findings from a sample to a wider population.

Data Analysis - Qualitative

• Definition: The process of making meaning from non-numerical data.
• Forms: Interview transcripts, documents, open-ended survey responses, images and videos.
• Purpose: To understand people and situations by analyzing meaning and context.

Qualitative Data Analysis Methods

• Qualitative Content Analysis: Systematic analysis of the content of textual materials to identify patterns, themes, and relationships.
• Narrative Analysis: Treats the transcript as a story, following a specific sequence and answering the question "And then what happened?"
• Discourse Analysis: Focuses on written or spoken language, analyzing how it is used in a social context.
• Thematic Analysis: Identifies common themes and patterns from transcribed interviews and focus groups.
• Grounded Theory: A systematic approach to developing a theory from qualitative data.
• Interpretive Phenomenological Analysis (IPA): Aims to understand people's unique experiences of a phenomenon.

Transcription of Data

• Interviews and focus groups are typically recorded and then transcribed.
• The transcription process involves writing a verbatim record of the recordings, including pauses, hesitations, laughs, etc.

Verification of Qualitative Data

• Verification ensures the reliability and validity of qualitative research.
• Several methods are used to verify qualitative data, including triangulation, reflective journals, data saturation, and member checking.
• Triangulation: Involves using multiple sources of data to check for consistency.
• Reflective Journal: A diary kept by the researcher to document personal thoughts, biases, and experiences.
• Data Saturation: Indicates that the researcher has collected enough data to support the study.
• Member Checking: Involves taking the data back to participants for feedback and confirmation.
• Self-Disclosure (Reflexivity): The researcher reflects on their own potential biases and how they might influence data.
• Meticulous Record-Keeping: Ensures transparency and consistency by documenting the decision-making process.

Homework Exercise

• Identify the six most popular qualitative data analysis methods: Qualitative content analysis, Narrative analysis, Discourse analysis, Thematic analysis, Grounded theory, Interpretive phenomenological analysis.
• Explain the concept of social constructionism: The idea that social phenomena are not objective realities, but rather products of social interaction and shared understanding within a culture.
• Why is gender a social construct? Gender roles and expectations are socially created and vary across cultures and time periods.
• What is triangulation? A data verification method that involves using multiple sources of data to check for consistency.
• Why is data verification important in qualitative research? To ensure the reliability, validity, and trustworthiness of the findings.

Homework Exercise: Part 2

• Which method of analysis would be most suited to understanding the personal experiences of young adults raised by a parent with a mental health problem? Interpretive Phenomenological Analysis (IPA) would be most suitable for exploring their unique experiences and perspectives.
• What is the relationship between the number of hashtags and likes on TikTok? Researchers found that a higher number of hashtags was related to more likes.

This quiz explores the critical concepts of data collection and the four levels of measurement: nominal, ordinal, interval, and ratio. Additionally, it covers quantitative and qualitative data analysis, including descriptive and inferential statistics. Test your understanding of these fundamental research principles.