Hello wizards, First of all, I'm a physicist and therefore I'm not much used to use statistics. So, please forgive me if this is a FAQ or stupid, but I failed to find the answer by myself. I have used "runs.test" (Package tseries) for computes the runs test for randomness , but I get this result: Runs test -1.8732 P-value = 0.0610 Alternative Hypothesis : Two sided How can I interpret this result ? Generally, one rejects the null hypothesis if the p-value is smaller than or equal to the significance level,but I have examined the documentation but I don't find the significance level. Thanks in advance. -- Web Page http://geocities.com/lord_tyranus_96/
Since no reply has been posted yet I will give it a shot. runs.test uses the normal approximation and in your case it returned a z score of -1.8732. This z score has a cumulative probability of pnorm(-1.8732,0,1) [1] 0.03052039 If you are concerned about having too many runs and too few runs you would select the "two.sided" option for runs.test, which gives a p-value of 0.0610 (0.0305 in each tail of the normal distribution). If you are concerned only with too few runs you would select the "less" option, which will give a p-value of 0.0305. Finally, if you are concerned only with too many runs you would select the "greater" option which will give a p-value of 1-0.0305 0.9693. If your significance level is 0.05, you would compare 0.05 to 0.0610 and not reject the null hypothesis for the two-sided case and compare 0.05 to 0.0305 in the one-sided case and reject the null hypothesis. Note that the normal approximation is OK for large samples but may give unacceptable results for small samples. I am unaware of any packages in R that perform an exact runs test. Tom>I have used "runs.test" (Package tseries) for computes the runs test >for randomness , but I get this result: > >Runs test >-1.8732 P-value = 0.0610 > >Alternative Hypothesis : Two sided > >How can I interpret this result ?[[alternative HTML version deleted]]