Lets say I have a population of 500 datapoints, which is clearly not normal. (Please see attached text file for an example population). These datapoints can be assumed to be IID. Now, I get 30 more datapoints and want to test if these have been drawn (with replacement) from the population. I'm doing the followin:<br>
<br>1. Since the population is non-normal, I'm unable to use regular t-tests. I am trying to use Wilcoxon's rank sum test in R. I'm not sure if it only compares the new sample with the median of the population or does it also compare the central tendency of the dataset around the median. <br>
<br>2. I'm bootstrapping 5000 samples (resampling), of size 30 from the population and recording their means and standard deviations and trying to infer if my sample mean is within acceptable range. I'm using the concept of Law of Large Numbers, however, I'm not sure if this is an acceptable methodology.<br>
<br>Any thoughts on this will be great.<br>-Nandi<br clear="all"><br>-- <br>I'm a great believer in luck, and I find the harder I work the more I have of it. ~Thomas Jefferson<br><br>Subhrangshu Nandi<br>
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