1. Meta-analysis: A method for systematically combining relevant qualitative and quantitative data from
various selected studies to derive a single conclusion with enhanced statistical power.
2. Literature Review: A comprehensive examination of previously published studies that relate to a
specific topic.
3. Stratification Analysis: The process of dividing a population into homogeneous subgroups before
sampling.
4. Factor Analysis: A technique for expressing the values of observed data as functions of several
possible causes to determine which causes are most significant.
5. Sensitivity Analysis: A quantitative approach to risk analysis and modeling that assesses how
variations in uncertain project elements affect the overall objective, often visualized with a tornado
diagram.
6. Cluster Analysis: The process of grouping a set of objects in a way that maximizes similarity among
objects within the same group.
7. Odds Ratio Analysis: A measure of the relationship between exposure and outcome, which calculates
the odds of an outcome occurring with a specific exposure compared to its occurrence without that
exposure.
8. Dimensional Analysis: An analysis technique that ensures that physical quantities being added or
equated are expressed in terms of the same fundamental dimensions (e.g., mass, length, time) to derive
meaningful relations.
9. Bivariate Analysis: The analysis of two variables to determine the empirical relationship between
them.