Search results
Results from the WOW.Com Content Network
Exploratory data analysis is an analysis technique to analyze and investigate the data set and summarize the main characteristics of the dataset. Main advantage of EDA is providing the data visualization of data after conducting the analysis.
Causal analysis is the field of experimental design and statistical analysis pertaining to establishing cause and effect. [1] [2] Exploratory causal analysis (ECA), also known as data causality or causal discovery [3] is the use of statistical algorithms to infer associations in observed data sets that are potentially causal under strict assumptions.
Pages in category "Exploratory data analysis" The following 13 pages are in this category, out of 13 total. This list may not reflect recent changes. ...
Data mining is a particular data analysis technique that focuses on statistical modeling and knowledge discovery for predictive rather than purely descriptive purposes, while business intelligence covers data analysis that relies heavily on aggregation, focusing mainly on business information. [4]
Exploratory Factor Analysis Model. 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 between measured variables. [1]
Exploratory research is "the preliminary research to clarify the exact nature of the problem to be solved." It is used to ensure additional research is taken into consideration during an experiment as well as determining research priorities, collecting data and honing in on certain subjects which may be difficult to take note of without exploratory research.
For a discussion of how the underlying conceptualization of exploratory research, descriptive research and explanatory research fit together, see: Conceptual framework.) Descriptive research can be statistical research. The main objective of this type of research is to describe the data and characteristics of what is being studied.
Exploratory data analysis (EDA) relies heavily on such techniques. They can also provide insight into a data set to help with testing assumptions, model selection and regression model validation, estimator selection, relationship identification, factor effect determination, and outlier detection. In addition, the choice of appropriate ...