The UNIVARIATE Procedure
- Overview
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Getting Started
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Syntax
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Details
Missing Values Rounding Descriptive Statistics Calculating the Mode Calculating Percentiles Tests for Location Confidence Limits for Parameters of the Normal Distribution Robust Estimators Creating Line Printer Plots Creating High-Resolution Graphics Using the CLASS Statement to Create Comparative Plots Positioning Insets Formulas for Fitted Continuous Distributions Goodness-of-Fit Tests Kernel Density Estimates Construction of Quantile-Quantile and Probability Plots Interpretation of Quantile-Quantile and Probability Plots Distributions for Probability and Q-Q Plots Estimating Shape Parameters Using Q-Q Plots Estimating Location and Scale Parameters Using Q-Q Plots Estimating Percentiles Using Q-Q Plots Input Data Sets OUT= Output Data Set in the OUTPUT Statement OUTHISTOGRAM= Output Data Set OUTKERNEL= Output Data Set OUTTABLE= Output Data Set Tables for Summary Statistics ODS Table Names ODS Tables for Fitted Distributions ODS Graphics Computational Resources
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Examples
Computing Descriptive Statistics for Multiple Variables Calculating Modes Identifying Extreme Observations and Extreme Values Creating a Frequency Table Creating Plots for Line Printer Output Analyzing a Data Set With a FREQ Variable Saving Summary Statistics in an OUT= Output Data Set Saving Percentiles in an Output Data Set Computing Confidence Limits for the Mean, Standard Deviation, and Variance Computing Confidence Limits for Quantiles and Percentiles Computing Robust Estimates Testing for Location Performing a Sign Test Using Paired Data Creating a Histogram Creating a One-Way Comparative Histogram Creating a Two-Way Comparative Histogram Adding Insets with Descriptive Statistics Binning a Histogram Adding a Normal Curve to a Histogram Adding Fitted Normal Curves to a Comparative Histogram Fitting a Beta Curve Fitting Lognormal, Weibull, and Gamma Curves Computing Kernel Density Estimates Fitting a Three-Parameter Lognormal Curve Annotating a Folded Normal Curve Creating Lognormal Probability Plots Creating a Histogram to Display Lognormal Fit Creating a Normal Quantile Plot Adding a Distribution Reference Line Interpreting a Normal Quantile Plot Estimating Three Parameters from Lognormal Quantile Plots Estimating Percentiles from Lognormal Quantile Plots Estimating Parameters from Lognormal Quantile Plots Comparing Weibull Quantile Plots Creating a Cumulative Distribution Plot Creating a P-P Plot
- References
References
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Blom, G. (1958), Statistical Estimates and Transformed Beta Variables, New York: John Wiley & Sons.
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Bowman, K. O. and Shenton, L. R. (1983), “Johnson’s System of Distributions,” in S. Kotz, N. L. Johnson, and C. B. Read, eds., Encyclopedia of Statistical Sciences, volume 4, 303–314, New York: John Wiley & Sons.
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Chambers, J. M., Cleveland, W. S., Kleiner, B., and Tukey, P. A. (1983), Graphical Methods for Data Analysis, Belmont, CA: Wadsworth International Group.
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Cohen, A. C. (1951), “Estimating Parameters of Logarithmic-Normal Distributions by Maximum Likelihood,” Journal of the American Statistical Association, 46, 206–212.
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Conover, W. J. (1999), Practical Nonparametric Statistics, Third Edition, New York: John Wiley & Sons.
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Croux, C. and Rousseeuw, P. J. (1992), “Time-Efficient Algorithms for Two Highly Robust Estimators of Scale,” Computational Statistics, 1, 411–428.
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D’Agostino, R. and Stephens, M. (1986), Goodness-of-Fit Techniques, New York: Marcel Dekker.
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Dixon, W. J. and Tukey, J. W. (1968), “Approximate Behavior of the Distribution of Winsorized
(Trimming/Winsorization 2),” Technometrics, 10, 83–98. -
Elandt, R. C. (1961), “The Folded Normal Distribution: Two Methods of Estimating Parameters from Moments,” Technometrics, 3, 551–562.
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Fisher, R. A. (1973), Statistical Methods for Research Workers, Fourteenth Edition, New York: Hafner Publishing.
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Fowlkes, E. B. (1987), A Folio of Distributions: A Collection of Theoretical Quantile-Quantile Plots, New York: Marcel Dekker.
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Hahn, G. J. and Meeker, W. Q. (1991), Statistical Intervals: A Guide for Practitioners, New York: John Wiley & Sons.
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Hampel, F. R. (1974), “The Influence Curve and Its Role in Robust Estimation,” Journal of the American Statistical Association, 69, 383–393.
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Iman, R. L. (1974), “Use of a
-Statistic as an Approximation to the Exact Distribution of the Wilcoxon Signed Rank Statistic,” Communications in Statistics, 3, 795–806. -
Johnson, N. L., Kotz, S., and Balakrishnan, N. (1994), Continuous Univariate Distributions-1, Second Edition, New York: John Wiley & Sons.
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Johnson, N. L., Kotz, S., and Balakrishnan, N. (1995), Continuous Univariate Distributions-2, Second Edition, New York: John Wiley & Sons.
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Jones, M. C., Marron, J. S., and Sheather, S. J. (1996), “A Brief Survey of Bandwidth Selection for Density Estimation,” Journal of the American Statistical Association, 91, 401–407.
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Lehmann, E. L. (1998), Nonparametrics: Statistical Methods Based on Ranks, San Francisco: Holden-Day.
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Odeh, R. E. and Owen, D. B. (1980), Tables for Normal Tolerance Limits, Sampling Plans, and Screening, New York: Marcel Dekker.
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Owen, D. B. and Hua, T. A. (1977), “Tables of Confidence Limits on the Tail Area of the Normal Distribution,” Communication and Statistics, Part B—Simulation and Computation, 6, 285–311.
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Rousseeuw, P. J. and Croux, C. (1993), “Alternatives to the Median Absolute Deviation,” Journal of the American Statistical Association, 88, 1273–1283.
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Royston, J. P. (1992), “Approximating the Shapiro-Wilk’s W Test for Nonnormality,” Statistics and Computing, 2, 117–119.
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Shapiro, S. S. and Wilk, M. B. (1965), “An Analysis of Variance Test for Normality (Complete Samples),” Biometrika, 52, 591–611.
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Silverman, B. W. (1986), Density Estimation for Statistics and Data Analysis, New York: Chapman & Hall.
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Slifker, J. F. and Shapiro, S. S. (1980), “The Johnson System: Selection and Parameter Estimation,” Technometrics, 22, 239–246.
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Terrell, G. R. and Scott, D. W. (1985), “Oversmoothed Nonparametric Density Estimates,” Journal of the American Statistical Association, 80, 209–214.
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Tukey, J. W. (1977), Exploratory Data Analysis, Reading, MA: Addison-Wesley.
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Tukey, J. W. and McLaughlin, D. H. (1963), “Less Vulnerable Confidence and Significance Procedures for Location Based on a Single Sample: Trimming/Winsorization 1,” Sankhya A, 25, 331–352.
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Velleman, P. F. and Hoaglin, D. C. (1981), Applications, Basics, and Computing of Exploratory Data Analysis, Boston, MA: Duxbury Press.
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Wainer, H. (1974), “The Suspended Rootogram and Other Visual Displays: An Empirical Validation,” The American Statistician, 28, 143–145.