Research design and data sources

Learning objectives

• Distinguish primary from secondary data and quantitative from qualitative methods, and pick the right one for a planning question.
• Explain what the decennial census and the American Community Survey (ACS) each do well, and when to use each.
• Describe common sampling methods and the biases that undermine survey results.
• Explain the difference between validity and reliability, and use triangulation to strengthen findings.
• Choose a research design (descriptive, evaluative, cross-sectional, longitudinal, quasi-experimental) that fits the question.
• Use community-based methods, such as asset mapping and key informant interviews, to understand a place.
• Match planning questions to data sources beyond the census, and to the right census geography.
• Design a survey that avoids common wording problems, and explain how sample size affects the margin of error.
• Recognize the ethical duties that come with collecting data about people.

Key concepts

Start with the question, not the data

Good planning research starts with a clearly stated question: How many housing units will the city need by 2040? Why do residents avoid the new park? Which intersections have the most serious crashes? The question decides what data you need, how precise it must be, and which method fits. A common mistake, and a common exam trap, is to reach for a familiar dataset or method before deciding what you're actually trying to learn.

A research design spells out:

• the question and the decision it supports;
• the unit of analysis (people, households, parcels, census tracts, trips);
• the data sources and how they'll be collected;
• the method of analysis; and
• the limits of what the results can tell you.

12 more sections follow in the full lesson.