Exploratory Data Analysis

  title={Exploratory Data Analysis},
  author={S. Shekhar and Hui Xiong},
  booktitle={Encyclopedia of GIS},
We were together learning how to use the analysis of variance, and perhaps it is worth while stating an impression that I have formed-that the analysis of variance, which may perhaps be called a statistical method, because that term is a very ambiguous one — is not a mathematical theorem, but rather a convenient method of arranging the arithmetic. Just as in arith-metical textbooks — if we can recall their contents — we were given rules for arranging how to find the greatest common measure, and… Expand
We develop a method of testing linearity using power transforms of regressors, allowing for stationary processes and time trends. The linear model is a simplifying hypothesis that derives from theExpand
Visual analysis of self-organizing maps
In the article, an additional visualization of self-organizing maps (SOM) has been investigated. The main objective of self-organizing maps is data clustering and their graphical presentation.Expand
Memory association machine: an account of the realization and interpretation of an autonomous responsive site-specific artwork.
This thesis is an account of the realization and interpretation of the autonomous responsive electronic media artwork “Memory Association Machine” (MAM). Realization and interpretation are componentsExpand
A Survey of Methods for Multivariate Data Projection, Visualisation and Interactive Analysis
In this paper, algorithms for multivariate data projection , based on topology or distance preserving map-pings, as well as tools and techniques for projection display and user interaction are brieeyExpand
A New Challenge for Information Mining
In the field of "Data Exploration" many approaches have been developed to solve the problem of management of big data that are also semantically rich. Nowadays, there is a strong need to support theExpand
Interfaces and Visual Analytics for Visualizing Spatio-Temporal Data with Micromaps
This research modifies the hierarchical Bayesian matrix model developed by Hooten et al. Expand
The current version of the toolbox (and accompanying user- friendly program) includes:-Real-time visualization of the power spectra, using short- time Fourier transforms-Real-time visualization of a SOM mapping of the sound (using SOMTOOLBOX for MATLAB
The underwater acoustics research group at the Portuguese Naval academy has been working for some years on unsupervised classification of underwater sound [1-3]. Some software was developed usingExpand
Investigation of crowdfunding in terms of innovative SME financing in a German context
The purpose of this mixed-methods study was to answer the following four questions: (RQ1) What is the percentage of crowdfunding in the overall funding of SMEs? (RQ2) Is there a statisticallyExpand
Outlier Detection over Sliding Windows for Probabilistic Data Streams
The problem of detecting an outlier over a set of possible world instances is equivalent to the problem of finding the k-th element in its neighborhood and a dynamic programming algorithm is proposed to reduce the detection cost from O(2|R( e; d) to O(|k·R(e; d)|), where E is the d-neighborhood of e. Expand
Forecasting and Reanalysis in the Monterey Bay/California Current Region for the Autonomous Ocean Sampling Network-II Experiment
Abstract During the August–September 2003 Autonomous Ocean Sampling Network-II experiment, the Harvard Ocean Prediction System (HOPS) and Error Subspace Statistical Estimation (ESSE) system wereExpand


-2 -> original^3, 0.5 -> sqrt(original), 2 -> 1/original • Combining several variables • Normalize measurements
  • 2005
• Interactive Data Analysis, Hoaglin (1977) • The ABC's of EDA
  • 1981
• Exploratory Data Analysis, Tukey, (1977) • Data Analysis and Regression
  • 1977
Newcomb 1881) The logarithms of the values (not the values themselves) are uniformly randomly distributed
  • Newcomb 1881) The logarithms of the values (not the values themselves) are uniformly randomly distributed
  • 1938
> (abs(preen -m) < s) + 0
  • > (abs(preen -m) < s) + 0
> round(sum(abs(preen -m) < 2 * s)/n * 100)
  • > round(sum(abs(preen -m) < 2 * s)/n * 100)
> round(sum(abs(preen -m) < 3 * s)/n * 100)
  • > round(sum(abs(preen -m) < 3 * s)/n * 100)
> round(sum(abs(preen -m) < s)/n * 100)
  • > round(sum(abs(preen -m) < s)/n * 100)
> sum(abs(preen -m) < 2 * s)
  • > sum(abs(preen -m) < 2 * s)
> sum(abs(preen -m) < 3 * s)
  • > sum(abs(preen -m) < 3 * s)