Timeline for Confidence interval for the confidence interval?
Current License: CC BY-SA 3.0
9 events
| when toggle format | what | by | license | comment | |
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| Feb 9, 2016 at 20:23 | comment | added | Guy Davidson | Mark, that makes a ton of sense, and I think it's similar to Glen's answer below. Right? | |
| Feb 8, 2016 at 2:22 | answer | added | Glen_b | timeline score: 5 | |
| Feb 8, 2016 at 1:50 | comment | added | Mark L. Stone | (continued) Presuming you have M i.i.d replications of forming confidence intervals based on n = 100 sample size, you can form the confidence interval for coverage probability based on binomial fraction of intervals containing the population mean. | |
| Feb 8, 2016 at 1:44 | comment | added | Mark L. Stone | I think what you essentially want to do is form a confidence interval for the coverage probability. The coverage probab9ility is the probability that any one confidence interval contains the population mean. | |
| Feb 8, 2016 at 0:07 | history | tweeted | twitter.com/StackStats/status/696485403377934336 | ||
| Feb 7, 2016 at 23:50 | comment | added | rep_ho | and it's turtles all the way down | |
| Feb 7, 2016 at 22:25 | comment | added | Jean-Paul | In that situation, wouldn't you take the average of all confidence intervals to improve your estimate? As a theoretical answer to your question, you can always create a confidence interval as long as you can (1) make an assumption about the underlying distribution, (2) have a mean, (3) have a variance, (4) have a confidence level. | |
| Feb 7, 2016 at 22:24 | review | First posts | |||
| Feb 7, 2016 at 22:28 | |||||
| Feb 7, 2016 at 22:21 | history | asked | Guy Davidson | CC BY-SA 3.0 |