similar to: Right shift for normality

Good Night I made different test to check normality and multinormality in my dataset, but I don´t know which test is better. To verify univariate normality I checked: shapiro.test, cvm.test, ad.test, lillie.test, sf.test or jaque.bera.test and To verify multivariate normal distribution I use mardia, mvShapiro.Test, mvsf, mshapiro.test, mvnorm.e. I have a dataset with almost 1000 data and 9

Dear all, I would like to know which is the right way to check the normality assumption for performing ANOVA. How do you check normality for the following example? I did an experiment where people had to evaluate on a 7 point scale, the degree of realism of some stimuli presented in 2 conditions. The problem is that if I check normality with the Shapiro test I get that the data are not

Hi everybody, somehow i dont get the shapiro wilk test for normality. i just can?t find what the H0 is . i tried : shapiro.test(rnorm(5000)) Shapiro-Wilk normality test data: rnorm(5000) W = 0.9997, p-value = 0.6205 If normality is the H0, the test says it?s probably not normal, doesn ?t it ? 5000 is the biggest n allowed by the test... are there any other test ? ( i know qqnorm

Hello, can someone give me an example of how to fit a linear model where the response is a matrix, please? (other than a loop over lm calls) The ?lm points me to model.matrix but it is not clear to me how to use a model matrix in an lm call. fit<-lm(headmatrix ~ tailmatrix) causes problems as soon as I use predict(fit,newframe). The variables in tailmatrix are not found in

Hi, I have found quite a few posts on normality checking of response variables, but I am still in doubt about that. As it is easy to understand I'm not a statistician so be patient please. I want to estimate the possible effects of some predictors on my response variable that is nº of males and nº of females (cbind(males,females)), so, it would be:

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Hi, this is my first help request so please bear with me. I've been running some normality tests using the nortest package. For some of my datasets the Cramer-von Mises normality test generates an extremely high probability (e.g., 1.637e+31) and indicates normality when the other tests do not. Is there something I'm misunderstanding or potentially a bug in the code? Below are the

Didn''t think I''d be back so quick with another question but here goes: In this recipe for the signin or login (as I call it) there are these two lines if the user authenticates correctly: session[:user] = user.id redirect_to :action => session[:intended_action], :controller => session[:intended_controller] So I''m not seeing anything in the way of an explanation

Hi, I am looking for a normality test in R to see if a vector of data I have can be assumed to be normally distributed and hence used in a linear regression. > help.search("normality test") suggests the Shapiro test, ?shapiro.test. Now maybe I am interpreting things incorrectly (as is usually the case), am I right in assuming that this is a composite test for normality, and hence a

I am conducting an experiment with four independent variables each of which has three or more factor levels. The sample size is quite large i.e. several thousand. The dependent variable data does not pass a normality test but "visually" looks close to normal so is there a way to compute the affect this would have on the p-value for ANOVA or is there a way to perform an nonparametric test

The normality of the residuals is important in the inference procedures for the classical linear regression model, and normality is very important in correlation analysis (second moment)... Washington S. Silva > Thank you all for your replies.... they have been more useful... well > in my case I have chosen to do some parametric tests (more precisely > correlation and linear regressions

My stat textbook tells me that using Shapiro-Wilk test for each variable one by one is not equal to a test for multivariate normality as a whole. Does R have a function of testing for multivariate normality? Thanks. Hongsheng (Hank) Liao, Ph.D. Lab Manager Center for Quantitative Fisheries Ecology 800 West 46th Street Old Dominion University Norfolk, Virginia 23508 Phone:757.683.4571

Dear Sir, I am writing to inquire about normality test given in nortest package. I have a random data set consisting of 300 samples. I am curious about which normality test in R would give me precise measurement, whether data sample is following normal distribution. As p value in each test is different in each test, if you could help me identifying a suitable test in R for this medium size of

Hi all, I have two very large samples of data (10000+ data points) and would like to perform normality tests on it. I know that p < .05 means that a data set is considered as not normal with any of the two tests. I am also aware that large samples tend to lead more likely to normal results (Andy Field, 2005). I have a few questions to ensure that I am using them right. 1) The Shapiro-Wilk

Hi all, I'm running a vector-time series model with the vars package. When I test the univariate and multivariate normality of the residuals using normality(), I get the results, but also this warning Warning messages: 1: longer object length is not a multiple of shorter object length in: b2 - rep(3, 4) 2: longer object length is not a multiple of shorter object length

I am having a hard time interpreting the results of the 'shapiro.test' for normality. If I do ?shapiro.test I see two examples using rnorm and runif. When I run the test using rnorm I get a wide variation of results. Most of this may be from variability of rnorm, samll sample size (limited to 5000 for the test), etc but if I repeat the test multiple times I can get: >

Hello All, I am new to R, and I am writing to seek your advice on how best to use it to run R's various normality tests in an automated way. In a nutshell, my situation is as follows. I work in an investment bank, and my team and I are concerned that the assumption we make in our models that the returns of assets are normally distributed may not be justified for certain asset classes. We are

Dear all, I'm a beginner of R and I need to carry out some three-way mixed ANOVAs. Following examples at http://personality-project.org/r/r.anova.html, I managed to get the ANOVA part, but I don't know how can I check data normality and homogeneity of variance in R (since they're the required assumptions of ANOVA analysis). Are there any special command/packages? Could anyone give me

I was wondering if it was possible to do a normality test on a very large sample dataset. It is approx. 160,000 residual estimates from meshes modelling the brain surfaces of 50 subjects (25 patients). shapiro.test only works with at most 5000 points. Are there issues with very large samples sizes that I should be aware of? Cheers, -Morgan

Hello, Do you know a R implemented normality test like the shapiro test but more suitable for large data set ? Thanks, _________________________________________________________________ Découvrez toutes les possibilités de communication avec vos proches [[alternative HTML version deleted]]