Preparing graphs is an essential part of data analysis and representation. Although psychologists use graphs extensively, most introductory statistics and research methods textbooks provide a limited review of good techniques for designing graphs. In this article, I briefly review the research on graphical techmquesand references on graphing.
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References
1.
American Psychological Association. (1994). Publication manual of the American Psychological Association (4th ed.). Washington, DC: Author.
2.
BarfieldW.RoblessR. (1989). The effects of two and three-dimensional graphics on the problem-solving performance of experienced and novice decision makers. Behaviour and Information Technology, 8, 369–385.
3.
BertinJ. (1983). Semiology of graphs (BergW. J., Trans.). Madison: University of Wisconsin Press.
4.
BowenR. W. (1992). Graph it! Englewood Cliffs, NJ: Prentice Hall.
5.
BurlerD. L. (1993). Graphics in psychology: Pictures, data, and especially concepts. Behavior Research Methods. Instruments. & Computers, 25, 81–92.
6.
CarswellC. M.FrankenbergerS.BemhardD. (1991). Graphing in depth: Perspectives on the use of three-dimensional graphs to represent lower-dimensional data. Behaviour and information Technology, 10, 459–474.
7.
ChambersJ. M.ClevelandW. S.KleinerB.TukeyP. A. (1983). Graphical methods for dam analysis. Belmont, CA: Wadsworth.
8.
ClevelandW. S. (1984a). Graphs in scientific publications. The American Statistician, 38, 261–269.
9.
ClevelandW. S. (1984b). Graphical methods for data presentation: Full scale breaks, dot charts, and multibased logging. The American Statistician, 38, 270–280.
10.
ClevelandW. S. (1994). The elements of graphing data (rev. ed.). Summit, NJ: Hobart.
11.
ClevelandW. S.DiaconisP.McGillR. (1982). Variables on scatter plots look more highly correlated when the scales are increased. Science, 216, 1138–1141.
12.
ClevelandW. S.McGillR. (1984). Graphical perception: Theory, experimentation, and application to the development of graphical methods. Journal of the American Statistical Association, 79, 531–554.
13.
ClevelandW. S.McGillR. (1985). Graphical perception and graphical methods for analyzing scientific data. Science, 229, 828–933.
14.
ClevelandW. S.McGillR. (1986). An experiment in graphical perception. International Journal of Man-Machine Studies, 25, 491–500.
15.
CoxD. R. (1978). Some remarks on the role of statistics of graphical methods. Applied Statistics, 27, 4–9.
16.
CroxtonF. E. (1927). Further studies in the graphic use of circles and bars II: Some additional data. Journal of the American Statistical Association, 22, 36–39.
17.
CroxtonF. E.StrykerR. E. (1927). Bar charts versus circle diagrams. Journal of the American Statistical Association, 22, 473–482.
18.
EllisW. C. (1926). The relative merits of circles and bars for representing component parts. Journal of the American Statistical Association, 21, 119–132.
19.
FisherH. T. (1982). Mapping information. Cambridge, MA: Abt Books.
20.
FriggeM.HoaglinD. C.IglewiczB. (1989). Some implementations of the boxplot. The American Statistician, 43, 50–54.
21.
FurlongM. J.WampoldB. E. (1982), Intervention effects and relative variation as dimensions in experts' use of visual inference. Journal of Applied Behavior Analysis, 15, 415–421.
22.
GouvierW. D.JacksonW. T.StussD. T.StethemL. L. (1992). Rapid visual data analysts in neuropsychological research: Box graphs. The Clinical Neuropsychologist, 6, 92–97.
23.
HenryG. T. (1993). Using graphical displays for evaluation data. Evaluation Review, 17, 60–78.
24.
HenryG. T. (1995). Graphing data: Techniques for display and analysis. Thousand Oaks, CA: Sage.
25.
HoaglinD. C.MostellerF.TukeyJ. W. (1991). Fundamentals of exploratory analysis of variance. New York: Wiley.
26.
KosslynS. M. (1985). Graphs and human information processing: A review of five books. Journal of the American Statistical Association, 80, 499–512.
27.
KosslynS. M. (1989). Understanding charts and graphs. Applied Cognitive Psychology, 3, 185–226.
28.
KosslynS. M. (1994). Elements of graph design. New York: Freeman.
29.
LoftusG. R. (1993). A picture is worth a thousand p values: On the irrelevance of hypothesis resting in the microcomputer age. Behavior Research Methods, Instruments, & Computers, 25, 250–256.
30.
MorleyS.AdamsM. (1991). Graphical analysis of single-case time series data. Brirish Journal of Clinical Psychology, 30, 97–115.
31.
OttenbacherK. J. (1986). Reliability and accuracy of visually analyzed graphed data from single-subject designs. The American Journal of Occupational Therapy, 40, 464–469.
32.
OttenbacherK. J. (1990). Visual inspection of single-subject data: An empirical analysis. Mental Retardation, 28, 283–290.
33.
SchmidtC. F. (1983). Statistical graphics. New York: Wiley.
34.
SmithA. F.PrenticeD. A. (1993). Exploratory data analysis. In KerenG.LewisC.A handbook for data analysis in the bekmoral sciences: Statistical issues (pp. 349–390). Hillsdale, NJ: Lawrence Erlbaum Associates, Inc.
StevensS. S. (1975). Psychophysics. New York: Wiley.
37.
StockW. A.BehrensJ. T. (1991). Box, line, and midgap plots: Effects of display characteristics on the accuracy and bias of estimates of whisker length. Journal of Educational Statistics, 16, 1–20.
38.
StussD. T.StethemL. L.PelchatG. (1988). Three tests of attention and rapid information processing: An extension. The Clinical Neuropsychologist, 2, 395–400.
39.
TufteE. R. (1983). The visual display of quantitative information. Cheshire, CT: Graphics Press.
40.
TufteE. R. (1990). Envisioning information. Cheshire, CT: Graphics Press.
41.
TukeyJ. W. (1977). Exploratory data analysis. Reading, MA: Addison-Wesley.
42.
Von HuhnR. (1927). Further studies in the graphic use of circles and bars I: A discussion of Ellis' experiment. Journal of the American Statistical Association, 22, 31–36.
43.
WainerH.ThissenD. (1993). Graphical data analysis. In KerenG.LewisC.A handbook for data analysis in the behavioral sciences: Statistical issues (pp. 391–457). Hillsdale, NJ: Lawrence Erlbaum Associates, Inc.