Qualitative Research

Qualitative research focuses on understanding concepts, experiences, and meanings from the perspective of individuals or groups. It deals with non-numerical data like words, images, or observations. The goal is to gain in-depth insights into a problem, explore complex phenomena, or generate new ideas and hypotheses. It often answers “why” or “how” questions.

• Characteristics:
  • Exploratory: It’s used when you want to understand something in detail or explore a topic that isn’t well understood.
  • Subjective: It seeks to understand subjective experiences, motivations, and perceptions.
  • Non-numerical data: Data is typically collected through interviews, focus groups, observations, or analyzing documents.
  • Smaller sample sizes: Often involves a limited number of participants, chosen for their specific experiences or expertise.
  • Flexible design: The research design can evolve as new insights emerge.
• Example: Imagine a study aiming to understand how cancer patients cope with emotional distress during chemotherapy. A qualitative researcher might conduct in-depth, semi-structured interviews with 15-20 cancer patients undergoing chemotherapy. The questions would be open-ended, such as: “Can you describe your emotional experience during chemotherapy?” “What strategies do you use to deal with stress or sadness?” “How does your support system influence your emotional well-being?” The researcher would analyze the interview transcripts for common themes, patterns, and narratives to gain a rich, nuanced understanding of their coping mechanisms and emotional journeys.

Quantitative Research

Quantitative research focuses on measuring variables, testing hypotheses, and establishing relationships using numerical data and statistical analysis. It aims to quantify problems, generalize findings to a larger population, and determine cause-and-effect relationships. It typically answers “what,” “when,” “where,” or “how many” questions.

• Characteristics:
  • Confirmatory/Explanatory: It’s used to test theories, confirm hypotheses, or establish generalizable facts.
  • Objective: It seeks to measure and analyze data objectively, often in controlled environments.
  • Numerical data: Data is collected through methods like surveys with closed-ended questions, experiments, or analyzing existing statistical databases.
  • Larger sample sizes: Often involves a large number of participants, typically selected randomly to ensure representativeness.