of data.The aim of this chapter is to offer the reader an overview of the most significant tools that can be used in a preliminary, exploratory phase, ranging from the most classical descriptive statistics meth
Exploratory data analysis is an investigative process in which you use summary statistics and graphical tools to get to know your data and understand what you can learn from them. With EDA, you can find anomalies in your data, such as outliers or unusual observations, uncover patterns, understan...
Cross-fertilisation between the fields of artificial neural networks and statistics has recently proved fruitful. In unsupervised learning, the realisation that simple neural network architectures are capable of performing classical statistical analysis has allowed insight into the operation of simple Hebbian ...
Exploratory Data Analysis Exploratory data analysis is concerned with visual displays of data, rather than with summary statistics and statistical significance tests that are based on deductive reasoning; this is discussed by Tukey. The aim of this approach is purely inductive: to explore the data se...
Communications in StatisticsM. Nakamura and V. P´erez-Abreu, Exploratory data analysis for counts using the empirical probability generating function, Commun. Stat., Theory Meth- ods 22 (3) (1993), 827-842.Nakamura, M. and P´erez-Abreu, V. (1993b). Exploratory Data Analysis for ...
DATA analysisGEOGRAPHIC spatial analysisDATA modelingAUTOCORRELATION (Statistics)Residual spatial autocorrelation is a situation frequently encountered in regression analysis of spatial data. The statistical problems arising due to this phenomenon are well ⿻恠tood. Original developments in the field of ...
Cross-fertilisation between the fields of artificial neural networks and statistics has recently proved fruitful. In unsupervised learning, the realisation that simple neural network architectures are capable of performing classical statistical analysis has allowed insight into the operation of simple Hebbian ...
Statgraphics proudly provides a suite of EDA techniques with its leading statistics and data analysis software. Learn about exploratory data analysis here!
Bivariate visualizations and summary statistics that allow you to assess the relationship between each variable in the dataset and the target variable you’re looking at. Multivariate visualizations, for mapping and understanding interactions between different fields in the data. ...
Journal of Computational & Graphical StatisticsJ. Camacho, R. A. Rodr´iguez-Go´mez, and E. Saccenti, "Group-wise principal component analysis for exploratory data analysis," Journal of Computational and Graphical Statistics, pp. 1-12, Dec. 2016....