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The rule of three is a method for calculating a 95% confidence interval when estimating $p$ from a set of $n$ IID Bernoulli trials with no successes. … Hence we have the probability of your confidence interval containing $p$ given by, $$0.05 \cdot 0 + 0.95^2 = 0.9025 \neq0.95.$$ Am I misunderstanding the rule of three? …

I'm using the Rule of Three to compute 95% CI $= [0, 3/n]$ for frequency of visits (in this case No. Visits $= 4$) which were not observed in the dataset. … However it occurred to me I could mechanically use the Rule of Three to compute 95% CIs $= [0, 3/n]$ extending for No. Visits $= 6$ all the way up to infinity. Is this reasonable? …

The rule of three in statistics states that if an event is binomially distributed and does not occur with in $n$ trials the maximum chance of it occurring is approximately $3/n$. … We might then decide to reason, ignoring the prior knowledge of the distribution, that the chance of black occurring is at most 3/10, which is not true. Is this a misapplication of the rule? …

I have a large population of data instances (say, 1000 instances) that are either of class1 or of class2. … I used the rule of three to determine that a 95% confidence interval for the percentage that an instance is of class1 is [0.94, 1]. …

I have three groups with very small sample sizes (6 obs per each group). … value for rule of thumb (checking the equality of variances/ Max variance/ min variance). …

This fact, sometimes called the "rule of three", is a consequence of the inequalities $$\exp\left(-\frac{np}{1-p}\right) \leq \Pr(X=0) \leq \exp(-np).$$ Do you know other such basic easy rules for statistics … This principle is not really a "rule of thumb" because it has a reliable theoretical foundation, but I don't see another tag for this question (I hope it is not off-topic) …

(Generalized Example: dice and we were given three linear combinations instead of actual frequencies after rolling it N times) (The expected value of the frequencies, instead of the probabilities, was … An example could be rolling a regular die and knowing only three linear combinations out of 100 rolls. The generalized rule of succession (link) is valid when the actual frequency count is known. …

I keep coming back to the rule of thumb offered by Burnham & Anderson 2004, pp. 270-272: Some simple rules of thumb are often useful in assessing the relative merits of models in the set: Models having … As an example, suppose that there are three candidate models, whose AIC values are 100, 102, and 110. …

The rule of three states that, if we observe $Y\sim \text{Bin}(n,p)$ to be 0, then $[0,3/n]$ is a 95% confidence interval for $p$. … My other, related question is: How do you verify the coverage probability for the interval, given that it's only defined for one possible value of $Y$? …

The general rule that people seem to use is to simply take $3/n$ (which in your case is 0.15%). This is sometimes called the "rule of three", and there are many questions here about this. … Revisiting the Rule of Three Is Rule of Three inappropriate in some cases? When to use (and not use) the rule of three and search the site. …

I found three sources of information: This suggests using 1.5, 3.5 and 9 as cutoffs. Here it is mentioned 1.5, 2.5 and 4.30. Chen (2010) suggests 1.68, 3.47 and 6.71. … For example, in the regression above, the "effect" of wt is negative, meaning that each increase of wt lowers the probability of the outcome. …

This rule of three is discussed at CV multiple times Is Rule of Three inappropriate in some cases? … , When to use (and not use) the rule of three, Using Rule of Three to obtain confidence interval for a binomial population and certainly more ... …

Let's say we have 10 students, where each student have been taught by one of three possible teachers. Then let us record how many hours each student spends studying and their scores in a given exam. … Is there a general rule of thumb that allow us to navigate this issue in more general contexts? …

Here is a paper on the rule of three in the clinical setting: https://onlinelibrary.wiley.com/doi/10.1111/j.1445-2197.2009.04994.x The bottom line is that the rule of three works quite poorly, but there … are better alternatives available at the click of a button! …

I use MCMC (Metropolis-Hastings) to sample posterior distributions of three parameters using a nonlinear least-squares objective function to calculate the likelihood of a parameter sets. … I suppose that with an autocorrelation time of 16 I can be sure that the Markov chain converged, but is there maybe some "rule of thumb" which tells me, given a chain of length 40000, which autocorrelation …