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Conceptual schema. A conceptual schema or conceptual data model is a high-level description of informational needs underlying the design of a database. [1][2] It typically includes only the core concepts and the main relationships among them. This is a high-level model with insufficient detail to build a complete, functional database. [3] It ...
Conceptual model. The term conceptual model refers to any model that is formed after a conceptualization or generalization process. [1][2] Conceptual models are often abstractions of things in the real world, whether physical or social. Semantic studies are relevant to various stages of concept formation.
Overview of a data-modeling context: Data model is based on Data, Data relationship, Data semantic and Data constraint. A data model provides the details of information to be stored, and is of primary use when the final product is the generation of computer software code for an application or the preparation of a functional specification to aid a computer software make-or-buy decision.
A statistical model is a mathematical model that embodies a set of statistical assumptions concerning the generation of sample data (and similar data from a larger population). A statistical model represents, often in considerably idealized form, the data-generating process. [1] When referring specifically to probabilities, the corresponding ...
A conceptual diagram of an additive multiple moderation model An example of a two-way interaction effect plot. If both of the independent variables are continuous, it is helpful for interpretation to either center or standardize the independent variables, X and Z. (Centering involves subtracting the overall sample mean score from the original ...
In statistics, path analysis is used to describe the directed dependencies among a set of variables. This includes models equivalent to any form of multiple regression analysis, factor analysis, canonical correlation analysis, discriminant analysis, as well as more general families of models in the multivariate analysis of variance and covariance analyses (MANOVA, ANOVA, ANCOVA).
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