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| bio | website | |
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| age | ||
| visits | member for | 2 years, 11 months |
| seen | Oct 8 '12 at 18:43 | |
| stats | profile views | 49 |
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Sep 30 |
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Using confidence interval from full sample to test statistics from a small sub-sample? In other words, what I am expecting to find is that the subgroup is not predictable and does not have the same distribution compared to the group at large, precisely because the subgroup is not random in a certain theoretically interesting way. |
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Sep 30 |
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Using confidence interval from full sample to test statistics from a small sub-sample? @MichaelChernick: Thank you for your comments. Let's say we don't know that Chicago is more democratic, and that's what we want to know. You find that 2/5 people in the state are democrats. You get a confidence interval, and then find that in Chicago the proportion is higher than that confidence interval, would it be valid to say that Chicago is in fact more democratic than the state at large? Keeping in mind that this is all from the same poll. I'm not trying to predict anything as such, but merely trying to tell if the subgroup is in fact significantly different from the group overall. |
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Apr 9 |
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Explaining to laypeople why bootstrapping works @cardinal Thanks, I updated the original post. Hopefully it is more clear. :) |
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Apr 9 |
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Explaining to laypeople why bootstrapping works I see, so if I understand you, then this technique assumes that the sample is an adequate model of the population, and therefore that resampling over that sample on a large enough scale will reveal something about the population, but only to the extent that the original sample is a good one. Now that I put it that way it seems almost obvious... |
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Apr 8 |
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Explaining to laypeople why bootstrapping works Thanks! This much I understand. I am particularly wondering how it is that resampling from a sample of the population helps to understand the underlying population. If we are resampling from a sample, how is it that we are learning something about the population rather than only about the sample? There seems to be a leap there which is somewhat counter-intuitive. |
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Feb 12 |
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Calculating p-value from an arbitrary distribution (I've done tests, and my data doesn't seem to be remotely normal.) |
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Feb 12 |
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Calculating p-value from an arbitrary distribution Actually, I'm not sure I quite follow how these functions work. The examples give results for a normal distribution, but where do I plug in my probability density function? |
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Feb 7 |
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Calculating p-value from an arbitrary distribution Yes, I think this is more in line with my current abilities. Thanks! |
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Feb 6 |
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Calculating p-value from an arbitrary distribution Ah! I get it. Thanks again. |
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Feb 6 |
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Calculating p-value from an arbitrary distribution Ok, this makes sense. I do have what I believe is a good estimation of the null distribution. Any hints on how to implement this in R? Thanks! |
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Jan 8 |
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Expected values for chi-squared test on binned paired counts Yes, that's what I am looking for. I have edited the question to reflect that. Please let me know if anything is unclear. |
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Dec 11 |
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Interpreting correlation from two linear mixed-effect models Ah, I see! Thanks. |
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Dec 11 |
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Interpreting correlation from two linear mixed-effect models Ah, I get it. Thank you! |
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Dec 10 |
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Interpreting correlation from two linear mixed-effect models @mpiktas: I have edited the question so that it includes the random effects only model. |
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Dec 10 |
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Testing paired frequencies for independence Wow, this looks really useful. I will acquire a copy of this book as soon as I can, since everyone seems to be citing it. In the meantime, just a naive question: can these models deal with an arbitrary number of random effects? I think I need 3 in my model. |
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Dec 10 |
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Interpreting correlation from two linear mixed-effect models @chl: Yes, it's the same data and basically the same hypothesis. |
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Dec 8 |
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Visualizing the distribution of something within a very large body of data Hah, good point. Well, let's say I could break this down into about 400 different groups? |
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Dec 7 |
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Testing paired frequencies for independence No, these are all different speakers as well. This data was taken from a corpus of recorded telephone conversations. So speaker A in conversation 1 is not the same person as speaker A in conversation 2. |
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Dec 7 |
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Testing paired frequencies for independence I did try this. But with so many 0s I am not sure what to make of it. I tried excluding any conversations in which either speaker used none of these constructions (i.e., the data point would fall along either axis), but the resulting Spearman correlation was not significant (and the coefficient was very small).. |
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Dec 7 |
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Testing paired frequencies for independence I also have the same data calculated relative to number of sentences spoken by each speaker in each conversation, if that makes a difference. |
