Search for "Exploratory data analysis" in article titles:

1. Methodology tutorial - exploratory data analysis: This is part of the methodology tutorial (see its table of contents). This tutorial will provide a short introduction to exploratory data analysis (EDA), multi-variate data reduction and related subjects. [100%] 2024-01-11 [research methodologies] [Research methodology tutorials]...

Suggestions for article titles:

1. Exploratory factor analysis: There are two main purposes or applications of factor analysis: Reduce data to a smaller set of underlying summary variables. For example, psychological questionnaires often aim to measure several psychological constructs, with each construct being measured by responses to several ... [92%] 2023-03-28 [{{PAGENAME}}]
2. Exploratory factor analysis: In multivariate statistics, exploratory factor analysis (EFA) is a statistical method used to uncover the underlying structure of a relatively large set of variables. EFA is a technique within factor analysis whose overarching goal is to identify the underlying relationships ... (Statistical method in psychology) [92%] 2023-04-07 [Factor analysis]
3. Exploratory causal analysis: Causal analysis is the field of experimental design and statistics pertaining to establishing cause and effect. Exploratory causal analysis (ECA), also known as data causality or causal discovery is the use of statistical algorithms to infer associations in observed data ... (Field in statistics pertaining to establishing cause and effect) [92%] 2023-12-16 [Exploratory data analysis]
4. Exploratory factor analysis: In multivariate statistics, exploratory factor analysis (EFA) is a statistical method used to uncover the underlying structure of a relatively large set of variables. EFA is a technique within factor analysis whose overarching goal is to identify the underlying relationships ... (Statistical method in psychology) [92%] 2024-07-16 [Factor analysis]
5. Data analysis: Data analysis is the process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names ... (The process of analyzing data to discover useful information and support decision-making) [90%] 2023-10-12 [Data analysis] [Data processing]...
6. Data analysis: Data analysis is the process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names ... (The process of analyzing data to discover useful information and support decision-making) [90%] 2023-10-06 [Data analysis] [Data processing]...
7. Data analysis: Data analysis is the process of looking at and summarizing data with the intent to extract useful information, make inferences, and develop conclusions. Using statistical or numerical software applications, data analysis can be pursued using a range of techniques, including ... [90%] 2024-05-07 [Research] [Statistics]...
8. Geometric data analysis: Geometric data analysis comprises geometric aspects of image analysis, pattern analysis, and shape analysis, and the approach of multivariate statistics, which treat arbitrary data sets as clouds of points in a space that is n-dimensional. This includes topological data ... [73%] 2023-10-12 [Multivariate statistics] [Spatial analysis]...
9. Combinatorial data analysis: In statistics, combinatorial data analysis (CDA) is the study of data sets where the order in which objects are arranged is important. CDA can be used either to determine how well a given combinatorial construct reflects the observed data, or ... [73%] 2023-10-12 [Combinatorics] [Data analysis]...
10. Functional data analysis: Functional data analysis (FDA) is a branch of statistics that analyses data providing information about curves, surfaces or anything else varying over a continuum. In its most general form, under an FDA framework, each sample element of functional data is ... [73%] 2023-12-25 [Statistical data types] [Statistical analysis]...
11. Forensic data analysis: Forensic Data Analysis (FDA) is a branch of Digital forensics. It examines structured data with regard to incidents of financial crime. (Social) [73%] 2023-12-19 [Digital forensics]
12. Functional data analysis: $ \def\cov{ {\rm cov}} $ $ \def\var{ {\rm var}} $ $ \def\ci{\cite} $ $ \def\cp{\citep} $ $ \def\eps{\varepsilon} $ $ \def\T{\mathcal{T}} $ $ \def\mt{\mathcal{T}} $ $ \def\xk{A_k} $ $ \def\xik{A_{ik}} $ $ \def\hxk{\hat{A}_k} $ $ \def\hxik{\hat ... (Mathematics) [73%] 2023-10-29 [Statprob]
13. Video Data Analysis: Video Data Analysis (VDA) is a curated multi-disciplinary collection of tools, techniques, and quality criteria intended for analyzing the content of visuals to study driving dynamics of social behavior and events in real-life settings. It often uses visual ... [73%] 2023-10-17 [Data analysis] [Techniques]...
14. Data-flow analysis: Template:Cleanup Data-flow analysis is a technique for gathering information about the possible set of values calculated at various points in a computer program. A program's control flow graph (CFG) is used to determine those parts of a ... [73%] 2023-12-18 [Compiler optimizations] [Static code analysis]...
15. Topological data analysis: In applied mathematics, topological data analysis (TDA) is an approach to the analysis of datasets using techniques from topology. Extraction of information from datasets that are high-dimensional, incomplete and noisy is generally challenging. (Analysis of datasets using techniques from topology) [73%] 2023-10-06 [Computational topology] [Data analysis]...
16. Symbolic data analysis: Symbolic data analysis (SDA) is an extension of standard data analysis where symbolic data tables are used as input and symbolic objects are made output as a result. The data units are called symbolic since they are more complex than ... (Extension of standard data analysis) [73%] 2023-10-11 [Data analysis] [Computational statistics]...
17. Social data analysis: Social data analysis is the data-driven analysis of how people interact in social contexts, often with data obtained from social networking services. The goal may be to simply understand human behavior or even to propagate a story of interest ... [73%] 2024-01-03 [Data visualization] [Collective intelligence]...
18. Social data analysis: Social data analysis is the data-driven analysis of how people interact in social contexts, often with data obtained from social networking services. The goal may be to simply understand human behavior or even to propagate a story of interest ... (Social) [73%] 2023-12-15 [Data visualization] [Collective intelligence]...
19. Data envelopment analysis: Data envelopment analysis (DEA) is a nonparametric method in operations research and economics for the estimation of production frontiers. DEA has been applied in a large range of fields including international banking, economic sustainability, police department operations, and logistical applications ... [73%] 2023-12-01 [Linear programming] [Production economics]...