13
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Revisiting the Rule of Three
The image below is how I look at confidence intervals. It is an adaptation from an image in the answer to the question 'The basic logic of constructing a confidence interval', which is itself an ...
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10
votes
Revisiting the Rule of Three
You can find some useful discussion of the "rule of three", including derivations and simulation analysis, in Javonovic and Levy (1997). With modern computing technology there is really no ...
- 133k
10
votes
Accepted
Rule of Thumb meaning in statistics
The term "rule of thumb" predates statistics. The most accepted theory of its origin is that people would measure things with their thumbs. Of course, this won't be exact, and, thus "...
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9
votes
Revisiting the Rule of Three
If you get no successes in (say) $n = 100$ trials, then you might
use a Jeffreys Confidence interval for the true binomial $p.$
This style of CI has very good frequentist properties, but its
...
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8
votes
Rule of Thumb meaning in statistics
van Belle book
Note an entire book: Statistical Rules of Thumb by Gerald van Belle.
https://onlinelibrary.wiley.com/doi/book/10.1002/9780470377963
I guess anybody with experience would rate some of ...
- 59.5k
7
votes
Relation between learning rate and number of hidden layers?
This question has been answered here:
With neural networks, should the learning rate be in some way
proportional to hidden layer sizes? Should they affect each other?
Short answer is yes, there ...
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7
votes
Rule of Thumb meaning in statistics
A rule of thumb is a heuristic:
(of an approach to problem solving, learning, or discovery) That
employs a practical method not guaranteed to be optimal or perfect;
either not following or derived ...
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5
votes
Accepted
How good an approximation is sampling with replacement to sampling without replacement?
My answer largely relates to the second part but I may come back with a few words on the first part later (once the notation in the question is clarified)
A common rule of thumb when approximating ...
- 291k
4
votes
Multiple Regression - Minimum Observations Per Dummy Variable
The question is "minimum number of observations to do what?". If the objective is to find the min number of observations needed to detect a significant effect of a dummy (when the effect truly exists),...
- 1,124
4
votes
Accepted
Academic reference on the "minimum of 5 expected counts per cell" rule of thumb for Chi-Square test?
Check the paper "The Tale of Cochran's Rule: My Contingency Table has so Many Expected Values Smaller than 5, What Am I to Do?" by P. M. Kroonenberg & Albert Verbeek.
Full citation: P. M....
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3
votes
Accepted
Is there a general rule of thumb for how big the ratio ( Sample size / parameters in model ) should be?
The 'one in ten rule' is often used as a rule of thumb, and it suggests 10 observations are needed for each variable being studies.
If you see a model that has substantially fewer observations per ...
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3
votes
Accepted
What is the logic behind "rule of thumb" for meaningful differences in AIC?
I encountered the same issue, and was trying to search an answer in related articles. The Burnham & Anderson 2002 (Model Selection and Multimodel Inference - A Practical Information-Theoretic ...
- 46
3
votes
Is Rule of Three inappropriate in some cases?
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 ...
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3
votes
Rule of thumb for using logarithmic scale
As a rule of thumb, try to make the data fit a (standard) normal distribution, a uniform distribution or any other distribution where the values are more or less “evenly” distributed.
As a ...
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3
votes
Relation between learning rate and number of hidden layers?
This is true, for instance, in linear networks. Consider the following product of $w\times w$ matrices
$$y=x W_1\ldots W_d$$
Now suppose our target labels are all 0's and we fit using least-squares ...
- 6,317
3
votes
What references should be cited to support using 30 as a large enough sample size?
This is meant to supplement user1108's answer stating that:
That said, the story told to me was that the only reason 30 was regarded as a good boundary was because it made for pretty Student's t ...
- 5,147
3
votes
Calculating optimal number of bins in a histogram
Conventional wisdom dictates that a "broken look' resulting from a histogram with many bins is undesirable. This clashes with the need to show individual outliers, digit preference, bimodality, ...
- 98.5k
3
votes
Accepted
What is the optimal sampling split for stratified sampling?
In this analysis we will assume that we are making an inference about the population by forming the Welch-T confidence interval for the population mean, which is the standard interval estimator. We ...
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2
votes
Rules of thumb for "modern" statistics
Try to be valiant rather than virtuous That is, don't let petty signs of non-Normality, non-independence or non-linearity etc. block your road if such indications need to be disregarded in order to ...
2
votes
Rules of thumb for "modern" statistics
I read this somewhere (probably on cross validated) and I haven't been able to find it anywhere, so here goes...
If you've discovered an interesting result, it's probably wrong.
It's very easy to ...
2
votes
Calculating optimal number of bins in a histogram
Please see this answer as a complementary of Mr. Rob Hyndman's answer.
In order to create histogram plots with exact same intervals or 'binwidths' using the Freedman–Diaconis rule either with basic R ...
2
votes
Rules of thumb for minimum sample size for multiple regression
I have found this rather recent paper (2015) assessing that just 2 observations per variable are enough, as long as our interest is on the accuracy of estimated regression coefficients and standard ...
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2
votes
How to judge skewness based on the mean and range?
There is a way that this would make some kind of sense
For a variable that's non-negative the minimum must be between 0 and the mean -- consequently if the range is many times as large as the mean ...
- 291k
2
votes
Accepted
Paper for the rule of thumb for homogenity of variances
Do you mean a rule of thumb involving the ratio of the maximum to minimum observed group variances being larger than a certain number k before we can conclude the assumption of homogeneity of ...
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2
votes
Number of observations for multiple linear regression
For this type of 3-level predictor you only would specify 2 dummy variables and have the 3rd (reference) level represented by having 0s for all the other levels. The reference level is thus ...
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2
votes
Prevalence upper bound when no events are observed in sample
You do not need any "rule of thumb" such as $\frac 3 n$, when you can compute it directly, using binomial confidence intervals.
You also should not use double sided CI's, as you want a "...
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2
votes
Prevalence upper bound when no events are observed in sample
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. (...
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1
vote
On the existence of rule of thumb for machine learning algorithms
There are a few rules of thumb found in Frank Harrell's Regression Modelling Strategies. If $p$ is the number of variables in the model, then the rule of thumb is to use between $p=m/10$ and $p=m/20$ ...
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1
vote
Equality of variances based on Rule of Thumb (for very small groups)
So you want to use anova with small sample size. Questions about that has been asked&answered here before, see this list.
With three groups and only 6 obs per group you essentially cannot test ...
- 82.8k
1
vote
Is there any rationale for rules of thumb for maxlag selection?
I never heard of rules of thumb for this, let alone theory rigorous ones, but it came to my mind that maybe you could calculate the ACF and use the largest significant lag as that max (or maybe some ...
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