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 data, it will be grateful.
I am neither a statistician nor an expert on these types of tests, but I'm guessing that your are unlikely to get a good answer even from people with such qualifications as such judgments can only be made in the context of a specific problem. You have not provided us with such a problem (please read the posting guide).
That admonishment aside, I typically start by using qqnorm() and qqline() to plot my data against the expected theoretical quantiles. If your data is perfectly normal, the points will fall right along the line. Skewness and deviations from normal by the tails produce very characteristic patterns in the plots which you can learn about by plotting some simulated data that is left-skewed, right-skewed, long tailed, or short tailed.
I personally find this graphical feedback to be a much more useful way to understand my data than doing a single normality test that produces a p-value. based upon assumptions I may not be privy to
For more, see the help by typing: ?qqnorm ?qqline Rob ------------------------------------------ Robert W. Baer, Ph.D. Professor of Physiology Kirksville College of Osteopathic Medicine A. T. Still University of Health Sciences 800 W. Jefferson St. Kirksville, MO 63501 660-626-2322 FAX 660-626-2965 ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
