This paper selectively reviews the field of scientific and medical graphics. Examples are provided using world health statistics and several new methods of presenting multiveriate data are introduced.
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References
1.
Cleveland WSGraphs in scientific publications. The American Statistician1984; 38: 26-19.
2.
Beniger JR, Robyn DLQuantitative graphics in statistics: A brief history. The American Statistician1978; 32: 1-11.
3.
Fienberg S.Graphical methods in statistics. The American Statistician1979; 33: 165-78.
4.
Snee RD, Pfeifer CGGraphical representation of data. In: Kotz S, Johnson NL eds, Encyclopedia of statistical sciences, New York: John Wiley, 1983.
5.
Gabriel KRMultivariate graphics. In: Kotz S, Johnson NL eds, Encyclopedia of statistical sciences, New York: John Wiley, 1985.
White JVUsing charts and graphs. New York: RR Bowker, 1984.
18.
Cleveland WSThe elements of graphing data. Monterey CA: Wadsworth, 1985.
19.
Velleman PF, Hoaglin DCApplications basics and computing of exploratory data analysis. Boston: Duxbury Press, 1981.
20.
Buja S., Fowlkes EB, Keramidas EM, Kettering JR, Lee JC, Swayne DF, Tukey PADiscovering features of multivariate data through statistical graphics. In: Proceedings of the Section on Statistical Graphics, Alexandria VI: American Statistical Association, 1986: 98-103.
21.
Donoho AW, Donoho DL, Gasko M.MACSPIN: dynamic graphical data (analysis on a desktop computer: the Apple Macintosh). In: Proceedings of the Section on Statistical Graphics, Alexandria VI: American Statistical Association, 1986: 86-91.
22.
McDonald JA , Pederson J.Computing environments for data analysis. I: Introduction. SIAM Journal of Scientific and Statistical Computing1985; 6: 1004-12.
23.
McDonald JA , Pederson J.Computing environments for data analysis. II: Hardware. SIAM Journal of Scientific and Statistical Computing1985; 6: 1013-2.
24.
McDonald JA , Pederson J.Computing environments for data analysis. III: Programming Environments. SIAM Journal of Scientific and Statistical Computing1988; 9: 380-400.
25.
Stuetzle W.Plot Windows. Journal of the American Statistical Association1987; 82: 466-75.
26.
Becker RA, Cleveland WS, Wilks ARDynamic graphics for data analysis. Statistical Science1987; 2: 355-95.
Scott DWStatistics in motion: where is it going? In: Proceedings of the Section on Statistical Graphics, Alexandria VI: American Statistical Association, 1989: 17-22.
29.
Haslett J., Bradley R., Craig P., Unwin A., Wills G.Dynamic graphics for exploring spatial data with application to locating global and local anomalies. The American Statistician1991; 45: 234-42.
Kosslyn SMImage and mind. Cambridge MA: Harvard University Press, 1980.
33.
Kosslyn SMGraphics and human processing. Journal of the American Statistical Association1985: 80: 499-512.
34.
Pinker S.A theory of graph comprehension. In: Friedle R eds, Artificial Intelligence and the future of testing . Norwood NJ. Ablex, 1990.
35.
Simken D., Hastie R.An information-processing analysis of graph perception. Journal of the American Statistical Association1987; 82: 454-65.
36.
Lewandowsky S. , Spence I.Discriminating strata in scatterplots. Journal of the American Statistical Association1989; 84: 682-88.
37.
Spence I.Visual psychophysics of simple graphical elements. Journal of Experimental Psychology: Human Performance and Perception1990; 16: 683-92.
38.
Spence I., Lewandowsky S.Graphical perception. In: Fox J, Long JS eds, Modern methods of data analysis . Newbury Park CA: Sage Publications , 1990: 13-57.
39.
Wilkinson L.An experimental evaluation of multivariate graphical point representations . Human Factors in Computer Systems: Proceedings . Gaithersburg MD, 1982: 202-9.
40.
Haber R., Wilkinson L.Perceptual components of computer displays. IEEE Computer Graphics and Applications1982; 2: 23-35.
41.
Wilkinson L., McConathy D.Memory for graphs. In Proceedings of the Section on Statistical Graphics, Alexandria VI: American Statistical Association, 1990: 25-32.
42.
Hochberg J., Krantz DHPerceptual properties of statistical graphs. In: Proceedings of the Section on Statistical Graphics, Alexandria VI: American Statistical Association, 1986: 29-35.
43.
Cleveland WSA model for graphical perception. In: Proceedings of the Section on Statistical Graphics, Alexandria VI: American Statistical Association, 1990: 1-24.
44.
Cleveland WS , Diaconis P., McGill R.Variables on scatterplots look more highly correlated when the scales are increased. Science1982; 216: 1138-41.
45.
Cleveland WS , McGill R.A color caused optical illusion on a statistical graph. The American Statistician1983; 37: 101-105.
46.
Cleveland WS , McGill R.Graphical perception: theory experimentation and application to the development of graphical methods. Journal of the American Statistical Association1984; 79: 531-54.
47.
Cleveland WS , McGill R.The many faces of a scatterplot. Journal of the American Statistical Association1984; 79: 807-22.
48.
Cleveland WS , McGill R.Graphical perception and graphical methods for analyzing and presenting scientific data. Science1985; 229: 828-33.
49.
Cleveland WS , McGill ME, McGill R.The shape parameter of a two-variable graph . Journal of the American Statistical Association1988; 83289-300.
50.
Tukey JWExploratory data analysis. Reading MA: Addison-Wesley, 1977.
51.
Sturges HAThe choice of a class interval. Journal of the American Statistical Association1926; 21:65.
52.
Doane DPAesthetic frequency classifications. The American Statistician1976; 30: 181-83.
53.
Scott DWOptimal and data-based histograms. Biometrika1979; 66: 605-10.
54.
Diaconis P. , Freedman D.On the maximum deviation between the histogram and the underlying density. Zeitschrift für Wahrscheinlichkeitstheorie1981; 57: 453-76.
Tarter ME, Kronmal RAAn introduction to the implementation and theory of nonparametric density estimation. The American Statistician1976 ; 30: 105-12.
57.
Silverman BWDensity estimation for statistics and data analysis. New York: Chapman & Hall, 1986.
58.
Wegman EJDensity estimation. In Kotz S, Johnson NL eds, Encylopedia of statistical sciences volume 2, New York: John Wiley, 1982: 309-15.
59.
Wand MP, Marron JS, Ruppert D.Transformations in density estimation. Journal of the American Statistical Association1991; 86: 343-53.
60.
Scott DWAveraged shifted histograms: effective non-parametric density desimators in several dimensions. The Annals of Statistics1985; 13: 1024-40.
61.
Frigge M., Hoaglin DC, Iglewicz B.Some implementations of the boxplot. The American Statistician1989; 43: 50-4.
62.
Shapiro SS, Wilk MBAn analysis of variance test for normality (complete samples)Biometrika1965; 52: 591-611.
63.
Iman R.Graphs for use with the Lilliefors Test for normal and exponential distributions . The American Statistician1982; 36: 109-12.
64.
Dallal GE, Finseth K.Double dual histograms. The American Statistician1977; 31: 39-41.
65.
Krieg AF, Beck JR, Bongiovanni MBThe dot plot: a starting point for evaluating test performance. Journal of the American Medical Association1988; 260: 3309-12.
Friedman JHExploratory projection pursuit. Journal of the American Statistical Association1987; 82: 249-66.
68.
Friedman JH , Stuetzle W.Projection pursuit regression. Journal of the American Statistical Association1981; 76: 817-23.
69.
Cleveland WS , Devlin S.Locally weighted regression: an approach to regression analysis by local fitting. Journal of the American Statistical Association1988; 83: 596-640.
70.
Gu C.Adaptive spline smoothing in non-gaussian regression models. Journal of the American Statistical Association1990; 85: 801-807.
71.
Breiman L. Theπ method for estimating multivariate functions from noisy data. Technometrics1991; 33: 125-43.
72.
Cleveland WSRobust locally weighted regression and smoothing scatterplots. Journal of the American Statistical Association1979; 74: 829-36.
73.
Hartigan JA : Printer graphics for clustering. Journal of Statistical Computation andSimulation1975 ; 4: 187-213.
74.
Becker RA, Cleveland WSTake a broader view of scientific visualization. Pixel1991; 2: 42-44.
75.
Hartigan JAClustering algorithms. New York: John Wiley, 1975.
76.
Wilkinson L.Permuting a matrix to a simple structure. Proceedings of the American Statistical Association, 1978.
77.
Ling RFA computer generated aid for cluster analysis. Communications of theACM1973; 16: 355-61.
78.
Chernoff H.The use of faces to represent points in k-dimensional space graphically. Journal of the American Statistical Association1973; 68: 361-68.
79.
Freni-Titulaer Lwj, Louv WCComparisons of some graphical methods for exploratory multivariate data analysis. The American Statistician1984; 38: 184-88.
80.
Wegman EJHyperdimensional data analysis using parallel coordinates. George Mason University Center for Computational Statistics and Probability Technical Report No. 1, 1986.
81.
Inselberg A.Discovering multi-dimensional structure using parallel coordinates. In: Proceedings of the Section on Statistical Graphics , Alexandria VI: American Statistical Association, 1989: 1-16.
82.
Andrews DFPlots of high dimensional data. Biometrics1972; 28: 125-36.
83.
Gabriel KRThe biplot graphic display of matrices with applications to principal components analysis. Biometrika1971; 58: 453-67.