mean这个词有许多用法和含义，在不同的情境下有不同的解释和表达方式。 以下是一些常见的用法： 1. 表示某物或某人的意图、目的或动机。 例如： - What do you mean? 你是什么意思？ - I mean to say that it's not fair. 我的意思是说这不公平。 - What does it mean when he says that?
So we have arithmetic mean (AM), geometric mean (GM) and harmonic mean (HM). Their mathematical formulation is also well known along with their associated stereotypical examples (e.g., Harmonic mea...
When studying two independent samples means, we are told we are looking at the "difference of two means". This means we take the mean from population 1 ($\\bar y_1$) and subtract from it the mean from
What do you mean by "the derivative at 1 SD is +- 1"? Derivative of what? If you mean of a density plot, then what distribution? The normal? Different distributions will have different derivatives at 1 SD from the mean.
"Can I use 'mean ± SD' for non-negative data when SD is higher than mean?" clearly you can (you already managed it in the question), the issue is more should you do so. However, what is missing here is the intended purpose of doing so. If it's really just to show both the mean and the standard deviation, wouldn't $\bar {x}=1, s = 3$ (whether or not the SD is larger) be less ambiguous and also ...
I also guess that some people prefer using mean squared deviation as a name for variance because it is more descriptive -- you instantly know from the name what someone is talking about, while for understanding what variance is you need to know at least elementary statistics. Check the following threads to learn more:
The mean of 0 and standard deviation of 1 usually applies to the standard normal distribution, often called the bell curve. The most likely value is the mean and it falls off as you get farther away.
5 it is possible to estimate mean and SD given the median and IQR? I am involved in a meta-analysis where some trials show outcomes as mean and standard deviation but most show median and inter-quantile range.
For a familiar (to some) example, the mean result of someone playing blackjack for one hour might be negative \$25 but with a standard deviation of say $100 (numbers for illustration). This large coefficient of variation makes it easier for someone to be tricked into thinking they are better than they really are.
