Generating Data with Identical Statistics but Dissimilar Graphics
@article{Chatterjee2007GeneratingDW, title={Generating Data with Identical Statistics but Dissimilar Graphics}, author={Sangit Chatterjee and Aykut Firat}, journal={The American Statistician}, year={2007}, volume={61}, pages={248 - 254} }
The Anscombe dataset is popular for teaching the importance of graphics in data analysis. It consists of four datasets that have identical summary statistics (e.g., mean, standard deviation, and correlation) but dissimilar data graphics (scatterplots). In this article, we provide a general procedure to generate datasets with identical summary statistics but dissimilar graphics by using a genetic algorithm based approach.
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References
SHOWING 1-6 OF 6 REFERENCES
Genetic Algorithms in Search Optimization and Machine Learning
- Computer Science
- 1988
This book brings together the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields.
Detection of Influential Observation in Linear Regression
- MathematicsTechnometrics
- 2000
A new measure based on confidence ellipsoids is developed for judging the contribution of each data point to the determination of the least squares estimate of the parameter vector in full rank…
A simple test for heteroscedasticity and random coefficient variation (econometrica vol 47
- Mathematics
- 1979
A simple test for heteroscedastic disturbances in a linear regression model is developed using the framework of the Lagrangian multiplier test. For a wide range of heteroscedastic and random…