Timeline for Are these data underdispersed? If so, what mechanisms may explain this?
Current License: CC BY-SA 3.0
21 events
| when toggle format | what | by | license | comment | |
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| S Nov 17, 2014 at 17:55 | history | bounty ended | Livid | ||
| S Nov 17, 2014 at 17:55 | history | notice removed | Livid | ||
| Nov 17, 2014 at 14:18 | vote | accept | Livid | ||
| Nov 10, 2014 at 23:39 | history | tweeted | twitter.com/#!/StackStats/status/531954427746201602 | ||
| Nov 10, 2014 at 19:28 | answer | added | Tom Minka | timeline score: 3 | |
| S Nov 10, 2014 at 18:11 | history | bounty started | Livid | ||
| S Nov 10, 2014 at 18:11 | history | notice added | Livid | Draw attention | |
| Nov 10, 2014 at 17:16 | history | edited | Livid | CC BY-SA 3.0 |
fixed typos
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| Nov 8, 2014 at 3:25 | comment | added | Livid | @whuber Sorry, I cannot risk revealing the data/purpose at this point. As I said, use the free throw scenario. I found it very difficult to find examples of processes that lead to underdispersion regarding any subject matter, so would welcome any examples. So, please do three models. Even if they are not relevant to my description of the system on first glance I am still interested. | |
| Nov 8, 2014 at 3:10 | comment | added | whuber♦ | Any "process that can result in this type of data" which incorporates random variables is a probability model. I can hypothesize loads of such models, but without specific information concerning the actual subject matter any of these would be pure speculation. | |
| Nov 8, 2014 at 2:39 | comment | added | Livid | @whuber Ah, no that is not the problem here. I used that phrase to mean "the maximum performance achievable by the individual". | |
| Nov 8, 2014 at 2:05 | comment | added | whuber♦ | If the data reflect maxima of sets of values, then they will tend to be narrowly dispersed and a little negatively skewed. A binomial model will not describe them. | |
| Nov 8, 2014 at 0:26 | comment | added | Livid | @whuber On rereading I realized I do not follow you here. Can you expand on this statement "Max performance level achieved"... suggests that data might not appropriately modeled as an iid Binomial sample. | |
| Nov 7, 2014 at 20:50 | history | edited | Livid | CC BY-SA 3.0 |
response to comment
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| Nov 7, 2014 at 20:18 | comment | added | gung - Reinstate Monica | We may not be able to identify the mechanism that produces your results. The autocorrelation idea is interesting. To investigate it you will need to get the trial by trial data from your study, or run a new study to get such data. | |
| Nov 7, 2014 at 20:08 | history | edited | Livid | CC BY-SA 3.0 |
clarified in response to comments
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| Nov 7, 2014 at 19:33 | comment | added | whuber♦ | Thanks for the update. "Max performance level achieved" may be a key phrase, because it suggests that data might not appropriately modeled as an iid Binomial sample. Unfortunately, your question about "mechanisms" cannot be answered until you disclose what the data really represent! The factors that might affect consistency of free throw performance will be largely different than those that affect consistency of ranks in a series of races, for instance. Having said that, there are plenty of ways to construct probability models of underdispersed phenomena. Maybe that's what you are looking for? | |
| Nov 7, 2014 at 19:28 | history | edited | Livid | CC BY-SA 3.0 |
completed question
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| Nov 7, 2014 at 18:58 | comment | added | whuber♦ | The only question that appears in all this is #1, whose answer you obviously already know. What do you really want to ask? Whether this dataset looks significantly underdispersed (as suggested by the title)? What does the title mean by "mechanisms"? | |
| Nov 7, 2014 at 18:58 | history | edited | gung - Reinstate Monica | CC BY-SA 3.0 |
formatted; light editing
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| Nov 7, 2014 at 18:50 | history | asked | Livid | CC BY-SA 3.0 |