what is non random sampling?
913293
Regular or systematic sampling.  Often used to determine whether patterns in distribution of your target class are as expected.
23153
Assuming you mean some random numbers, try http://www.random.org
537896
http://www.php.net/manual/en/function.rand.php\nhttp://www.php.net/manual/en/ref.array.php\n\nNote, I haven't tested this code, but to get unique random numbers, do something like this:\n\n$numbers  = array();\n\nwhile (count($numbers) <10) {\n\n$rnum = rand(1,1000);\n\nif( array_search( $rnum,$numbers ) === false) {\n$numbers[] = $rnum;\n}\n\n}
735064
That sounds familiar... Think I'm working on it now! But I don't remember q. It is n in my book. In which case, q (if I'm thinking right) is the number of samples. Then again what's up with the ^'s? If np was > 10, then it meant that the distribution was approx. normal. You might be ahead of me right now...
947677
www.thefreesite.com/Free\n_Samples\n\nwww.all-free-samples.com
1152776
Depending on your computer type you can download or purchase programs that will allow you to 'chop up' samples as you please.  I've heard on of one, I just have to tell you the name.  It's for PC users by the way.  It's called Mr. Free Free.  I couldn't believe it when I saw it.  Funniest name for software I've seen.
761676
In theory there could likely be a true random number generator.  However, due to chaos, even a seemingly insignificant occurence can influence the outcome of the random number generator.  Add to that Huygens uncertainty principle in which any measurement of an object will affect its state, and you've doubly messed up the true randomness of the generator.
124804
For an uncertainty x of 0.01 (which your 99% accuracy would be) you need 1/x^2 samples which would be 10000.  This is true for a large population (>>10000).  I believe you still need that many for 20000 population but am only 99% sure.\nSource: Best recollection of a stat course 50 years ago.
902875
It sounds like random sampling... why?\nI am not sure what you mean, if it were simply, say, the first 100 names in the Manchester telephone system's number data base, then it would not be random because only a relatively few people whose last name began with an A would be included.\nNow, if all those numbers were mixed up in a hat, and the first 100 drawn were to be used, then the sample is random because anyone in the number data base could theoretically been chosen.\nLet's have a little fun with this. \nIt is impossible to sample, say all 110,000 chocolate bars made by a company in one month. However, quaity control wants to make sure each has a certain number of nuts in them\nSo as the bars are completed at end of the assembly line, once a week, a quality control person randomly grabs 100 bars and counts the nuts in it. Again, any of the 110,000 could have been chosen, but the person merely grabs 100 of them.\nThrough inferential statistics the company can estimate with high accuracy if all the candy bars produced have the right amount of nuts by merely counting nuts in 100 bars. The key: ALL bars had an equal chance of being selected; this is what made the sampling random.
9363
No.  You can't definitively "prove" a sequence of numbers is not randomly generated by just looking at the numbers, but you can still draw conclusions with a high degree of confidence.\n\nFor example, it is extremely unlikely that a random number generator will produce the same number twenty times in a row, but technically, it is possible.  So seeing this happen doesn't prove it's not random, but you can still conclude that it's not.
469948
Here are some websites with sample survey questions that you can use. You can simply adopt them to the specific needs you have:\n\nhttp://www.questionpro.com/sample/\nhttp://www.surveyconsole.com/questionnaire-samples.html
711252
These sites may help.  They seem to have some practice samples that are free.
397969
Random from pure sines? Only if you can add up an infinite number of them.\nI think, it can be "proved": if you will add only a finite number of sines, the result sum will be continuous for all x and then in sufficient small vicinity of point x it will be bounded by interval of any given length. In other words, values of finctions in points NEAR x will be NEAR value of function in x itself. So it couldn't be called "random".\n\nBut non-periodic is quite simple.\n\nsin(x) + sin(x*sqrt(2)) is non-periodic.\n\n\nPS. I'm just curious: why do you need REALLY genuine white noise? I think it has only theoretical meaning. For all practical tasks it's enough to use "pseudorandom" sequences.\nFor example, x_(n+1) = sin(x_n * 10^9).\nIt isn't uniformly distributed, but also exists a bit more complicated uniform ones.
803328
A representative sample should have the same characteristics of the population from which it is drawn.  For example, if you wanted to find out the average height of all Americans, a sample that included mostly basketball players would NOT be representative, nor would a sample that included only women. Instead, a representative sample would include people of various races, both sexes, and all ages--so it would have the same variety of heights that can be found in the whole population.\n\nStatistical theory says that the type of sample most likely to be representative is a random sample, a sample where random numbers or games of chance assure that every member in the population has an equal chance of being selected.  Since this is often impractical to do, other types of "good" (usually representative) samples include systematic samples (where you number off and, for instance, call every 100th name in the phone book) and stratified samples (where you carefully include various sub-groups, like people of all different races in your sample).\n\nAmong the least representative samples are internet polls, where anyone who wants to can answer.  Usually only those with strong opinions on a subject bother responding to such polls.
167090
Simulation technique is used to generate a no of random no so that these can be used to generate different scenarios and circumstances.\nMonte Carlo is one of the techniques to generate these nos.\nfind more on the following link \nhttp://www.decisioneering.com/monte-carlo-simulation.html
957260
this is not a question
238214
armnod\nIt's the letters of the word random in a random order. That's about as random as it gets.