# data[].attributes.body
📌 Purpose: To describe, explain, predict, investigate.

📌 Types:

•📊 Quasi-Experimental → Compares groups but lacks full control.

•📅 Cross-Sectional → Collects data at one point in time.

•📋 Survey → Uses questionnaires for numerical data.

📌 Key Approaches:

•✏️ Descriptive Research → Describes a situation without finding relationships.

•🔗 Correlational Research → Examines relationships between two variables (helps in prediction).

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📌 Purpose: To understand deeper meanings & abstract concepts.

📌 Types:

•📖 Case Study → In-depth study of 1 or a few individuals.

•🎯 Action Research → Practical research to improve a situation.

📌 Data Collection:

•👀 Observations

•🗣 Interviews

•📄 Document Analysis

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📌 Combines Quantitative & Qualitative approaches.

📌 Order of Use:

•Start with Qualitative → Explore deeply.

•Follow with Quantitative → Measure & validate findings.

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Descriptive Statistics → Summarizes data

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Descriptive Statistics → Summarizes data

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•Percentage

•Mean

•Mode

•Median

•Standard deviation

•Frequency

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Inferential Statistics → Draws conclusions from data

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Inferential Statistics → Draws conclusions from data

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•T-test → Compares means between groups

•Correlation → Finds relationships between variables

•Pearson

•Spearman

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Qualitative Research (Words & Meaning-Based)

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Qualitative Research (Words & Meaning-Based)

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•No focus on numerical statistics

•Uses observations, interviews, and document analysis instead

•More about themes, patterns, and deeper understanding

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Involves two groups:

1. Treatment Group (receives the intervention)

2. Control Group (does not receive treatment)