Data analysis in architecture research involves the systematic examination and interpretation of data collected through various sources and methods related to the study of architecture. It involves analyzing numerical data such as measurements, quantitative surveys, and statistics as well as qualitative data such as notes from field observations, interviews, and case studies. The aim is to identify patterns, trends, relationships, and insights that can help inform design practices and decisions. Examples of data analysis techniques include descriptive statistics, inferential statistics, content analysis, thematic analysis, and discourse analysis.
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