2019年4月8日 · On the other hand if your sample is a very small fraction of the population this barely makes a difference. A common rule of thumb that people use is to ignore it if the standard deviation is overestimated by less than:about 5%. This corresponds to the 10% rule you mention. Also see finite population correction.

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2023年1月29日 · In this problem the sample size is too small compared to the population. The sample is not independent so the 10% condition is violated. How does violating this condition effect the Standard Deviation of a sampling distribution of p.

2019年12月27日 · An important thing to understand about confounding is that it is generally on a dataset by dataset basis. This works with the 10% rule. Essentially, if the OR of your exposure/outcome relationship does not change by 10% or more after adding the third variable into the model, there is not good enough evidence of confounding to keep it in the model.

2012年12月10日 · $\begingroup$ I agree: I cannot conceive of any good justification for rule 3 and I can think of many exceptions. The (unpaired) t-test is notoriously sensitive to skewness and that "10% of population" threshold appears to be without foundation. $\endgroup$ –

I really don't like "The Ten Percent Rule". It doesn't make any sense at low mileages (taking four weeks to go from 10 to 15 miles) or high mileages (going from 100 to 146 miles over four weeks). I think the biggest problem is that our bodies don't react instantly to new stresses, so if you're running 30 mpw, then go out and run 33,36,39 and ...

2022年10月4日 · Another 10 percent said that their children were physically abused by their mate in the same last six months. How these figures compare to the national average is unclear . However, regardless of national data, it is disturbing to note that 40 percent of the officers stated that in the last six months prior to the survey they had gotten out of ...

2020年1月11日 · $\begingroup$ This 'condition' is not a condition, its a rule of thumb some people use. The logic goes "In this situation the dependence under random sampling without replacement is small enough that I'm willing to approximate the correct calculations by treating these as if they were sampled with replacement".

The idea of 30 trials is a rule of thumb, different fields have different accepted numbers also the varience of these events can also effect the number ofor recommended trials. That being said it is a useful rule of thumb, beware research or articles that have something like 5 trials where the article says this is the next big thing.

2023年9月6日 · I keep hearing about a rule that you can’t approve a member’s leave if it there’s already 10 percent or more people on leave at a time, but I can’t…