Social Research — Foundations of Social Research + 4 more topics

Social research is a systematic way of investigating and understanding social phenomena. It's not just about collecting information; it's about interpreting it within a theoretical framework and using rigorous methods to ensure your findings are trustworthy.

At its heart, social research aims to answer questions about people, groups, cultures, and institutions. This involves several key steps, often starting with a broad idea and narrowing down to specific questions you can investigate.

Formal scientific theory isn't just a hunch; it's a well-substantiated explanation of some aspect of the natural or social world, based on a body of facts that have been repeatedly confirmed through observation and experiment. It's often misunderstood as just an idea, but in science, a theory is a powerful and widely accepted framework.

Logic, in this context, is about how you reason and connect ideas. It helps you move from observations to conclusions in a systematic, defensible way. There are two main types of logical reasoning you'll use in social research:

When you're doing social research, you often start with big, abstract ideas, like "happiness," "social class," or "intelligence." These are called concepts. To study them scientifically, you need to make them precise.

In social research, formal scientific theory isn't just about big, grand ideas; it's a systematic approach to making sense of observations and predicting future events. It gives you a roadmap to connect abstract ideas with concrete data.

When you conduct social research, you're dealing with people's lives, opinions, and sensitive data. This means ethical considerations aren't just good practice; they're fundamental to the validity and trustworthiness of your work. Ignoring ethics can harm participants, invalidate your findings, and damage your reputation.

• Internal Validity: Is the observed effect in your study truly caused by your independent variable, or by something else? You ensure this by controlling for confounding variables.
• External Validity: Can your findings be generalized to other populations, settings, or times? This is about how widely applicable your results are.
• Construct Validity: Are your measures actually tapping into the theoretical concepts you're trying to study? For example, does your "happiness scale" truly measure happiness, or just a temporary mood?