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# [Ñ§Ï°×ÊÁÏ] Tests of Normality in SPSS [·ÖÏí]

hanszhu ·¢±íÓÚ 2006-5-1 22:16:00 |ÏÔÊ¾È«²¿Â¥²ã
 Dear Experts. When I need to check the normality I create the Kolmogoro-Smirnov test and if Sig <0.05, then the distribution is non-normal otherwise the distribution is normal. Please let me know if it is the right way or there is another way. Thanks. Omar.
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hanszhu ·¢±íÓÚ 2006-5-1 22:17:00 |ÏÔÊ¾È«²¿Â¥²ã
 Are you using 1-sample K-S test (Analyze -> Nonparametric tests ->1-sample K-S? It lacks power to detect non-normality. You should use either K-S with Lilliefors correction or Shapiro-Wilktest (this last methods is considered the best). Both are availablewith EXAMINE. See the following example: DATA LIST FREE/lead(F8.1).BEGIN DATA0.6 2.6 0.1 1.1 0.4 2.0 0.8 1.3 1.2 1.5 3.2 1.7 1.9 1.9 2.2 5.10.2 0.3 0.6 0.7 0.8 1.5 1.7 1.8 1.9 1.9 2.0 2.0 2.1 2.8 3.1 3.9END DATA.VARIABLE LABEL lead 'Lead concentration (µmol/24 h)'. * Shapiro-Wilk & K-S(Lilliefors) *.EXAMINEVARIABLES=lead/PLOT BOXPLOT STEMLEAF NPPLOT/COMPARE GROUP/STATISTICS DESCRIPTIVES/CINTERVAL 95/NOTOTAL. * One-sample K-S (not corrected) *.NPAR TESTS/K-S(NORMAL)= lead. There is quite a difference in significance between K-S andK-S(Lilliefors). HTH Marta [´ËÌù×ÓÒÑ¾­±»×÷ÕßÓÚ2006-5-1 22:17:36±à¼­¹ý]
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hanszhu ·¢±íÓÚ 2006-5-1 22:20:00 |ÏÔÊ¾È«²¿Â¥²ã
 Hello: I need to check for bivariate normality but am unclear about how to performthe procedure in SPSS. I have 33 variables in a data set in which I want torun factor analysis, but I know there is positive skewness from theunivariate analysis. Here are the specific questions for which I needadvice. 1. Can anyone tell me how to perform the bivariate analysis? If I run aregression on each pair of variables and request plots, which plots should Ibe concerned with? How do I save the residuals? And then, what should I dowith the residuals? 2.If my sample size is approximately 210 (presumably large), should Inot concern myself with multivariate normality? I have checked the SPSS archives and was unable to find more specificinformation on bivariate normality. Thus, I would greatly appreciate yourinsights on the topic. Thanks, Sealvie
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hanszhu ·¢±íÓÚ 2006-5-1 22:20:00 |ÏÔÊ¾È«²¿Â¥²ã
 I would suggest that you test multivariate normality using Mardia's PK statistic, which is available in the PRELIS package. There is a fairly large literature on the use and interpretation of this statistic. HTH, KS For personalized and professional consultation in statistics and researchdesign, visit www.statisticsdoc.com [´ËÌù×ÓÒÑ¾­±»×÷ÕßÓÚ2006-5-1 22:24:13±à¼­¹ý]
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hanszhu ·¢±íÓÚ 2006-5-1 22:22:00 |ÏÔÊ¾È«²¿Â¥²ã
 Sealvie, 1. For a SPSS macro to examine bivariate/multivariate normality have alook at: http://www.columbia.edu/~ld208/ 2. Also look at: http://www.stat.umn.edu/~drak0020/classes/5021/labs/bivnorm/ The author of this site (Douglas Drake) provided me with the followingcitations: @article{best:rayn:1988, Author = {Best, D. J. and Rayner, J. C. W.}, Title = {A Test for Bivariate Normality}, Year = 1988, Journal = {Statistics \& Probability Letters}, Volume = 6, Pages = {407--412}, Keywords = {Goodness-of-fit; Skewness; Kurtosis}} @article{maso:youn:1985, Author = {Mason, Robert L. and Young, John C.}, Title = {Re-examining Two Tests for Bivariate Normality}, Year = 1985, Journal = {Communications in Statistics, Part A -- Theory and Methods}, Volume = 14, Pages = {1531--1546}, Keywords = {Goodness-of-fit; Ring test; Line test}} @article{pett:1979, Author = {Pettitt, A. N.}, Title = {Testing for Bivariate Normality Using the Empirical Distribution Function}, Year = 1979, Journal = {Communications in Statistics, Part A -- Theory and Methods}, Volume = 8, Pages = {699--712}, Keywords = {Goodness of fit; Cramer-von Mises}} @article{vita:1978, Author = {Vitale, Richard A.}, Title = {Joint Vs. Individual Normality}, Year = 1978, Journal = {Mathematics Magazine}, Volume = 51, Pages = {123--123}, Keywords = {Bivariate normal distribution}} @article{mard:1975, Author = {Mardia, K. V.}, Title = {Assessment of Multinormality and the Robustness of {H}otelling's $T^2$ Test}, Year = 1975, Journal = {Applied Statistics}, Volume = 24, Pages = {163--171}, Keywords = {Bivariate distributions; Mahalanobis distance; Multivariate kurtosis; Multivariate skewness; Non-normality; Permutation test}} @article{kowa:1970, Author = {Kowalski, Charles J.}, Title = {The Performance of Some Rough Tests for Bivariate Normality Before and After Coordinate Transformations to Normality}, Year = 1970, Journal = {Technometrics}, Volume = 12, Pages = {517--544}, Keywords = {Goodness of fit} 4. John Marden wrote a paper on the use of various plots. It was to bepublished in Statistical Science some time in 2005. Bob Green
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hanszhu ·¢±íÓÚ 2006-5-1 22:26:00 |ÏÔÊ¾È«²¿Â¥²ã
 Happy Holidays to All: I have a data set where none of the variables that I wish to use in my regression analysis follows the normal distribution. Further some of these variables have extrme outliers (which may account for the violations of normality). What is the best way to deal with these outliers short of excluding them from the analysis given that they account for approx. 8% of the data and can I still run parametric tests even though the assumptions of normaality have been violated. Any help would be appreciated.
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hanszhu ·¢±íÓÚ 2006-5-1 22:34:00 |ÏÔÊ¾È«²¿Â¥²ã
 Hi The variables you are you talking about, are they dependent or independent?. For regression models, you don't need normally distributed independent (predictor) variables. Moreover, you don't even need that the dependent variable is normally distributed, what you need is that the residuals are normally distributed. Build your model, save the residuals and check their normality (either visually, with a histogram, or mathematically, with Shapiro-Wilk test) HTH Marta [´ËÌù×ÓÒÑ¾­±»×÷ÕßÓÚ2006-5-1 22:35:05±à¼­¹ý]
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hanszhu ·¢±íÓÚ 2006-5-1 22:36:00 |ÏÔÊ¾È«²¿Â¥²ã
 Hello all, regression analysis has the four assumptions which are: 1) the assumption oflinearity 2) the assumptions of independence 3) the assumption of constantvariance and 4) Normality From a practical viewpoint how do you test this assumptions? Are theremethods in SPSS that I can use for that. From the experimental procedure Ihave ensured that each measurement is independent by randomization. However,is ther a statistical method that can test if or even how well thisassumptions exists in the data? What about the other three assumptions? Kind Regards,Karl
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hanszhu ·¢±íÓÚ 2006-5-1 22:37:00 |ÏÔÊ¾È«²¿Â¥²ã