Timeline for Why does Central Limit Theorem break down in my simulation?
Current License: CC BY-SA 4.0
6 events
| when toggle format | what | by | license | comment | |
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| Mar 9, 2019 at 18:33 | comment | added | whuber♦ | @Henry Thank you for your comments. I wasn't making a remark about these particular circumstances, but only about the logic of this answer, in the hope that it could be explained further. | |
| Mar 9, 2019 at 16:51 | comment | added | Henry | @whuber Since the distribution of the first set looks left skewed, I would expect the sum of five also to be left skewed, in a less extreme way than I would expect the sum of five from the second set to be right skewed. To get the skewness to reduce further, I would have thought that you would need a larger sample size | |
| Mar 9, 2019 at 16:49 | comment | added | Henry | @whuber: I think you are saying that the normal distribution gives a reasonably good approximation for a sample of five from the first set. Since there are only an finite number of values for the sums (13 possible values without replacement and 21 possible values with replacement), the approximation does not get much better with a large number of samples of five, and the initial approximation is more due to the initial pattern... | |
| Mar 9, 2019 at 15:45 | comment | added | whuber♦ | That this cannot be a valid explanation is evident from the observation that the CLT gives a good approximation for the first set of data in the question, which is equally small. | |
| Mar 9, 2019 at 13:50 | review | Low quality posts | |||
| Mar 9, 2019 at 17:24 | |||||
| Mar 9, 2019 at 13:34 | history | answered | feynman | CC BY-SA 4.0 |