r - How to interpret a QQ plot? - Cross Validated
Since this thread has been deemed to be a definitive "how to interpret the normal q-q plot" StackExchange post, I would like to point readers to a nice, precise mathematical relationship …
normal distribution - KL divergence between two univariate Gaussians ...
I need to determine the KL-divergence between two Gaussians. I am comparing my results to these, but I can't reproduce their result. My result is obviously wrong, because the KL is not 0 for KL(p, ...
Is there an explanation for why there are so many natural phenomena ...
Mar 30, 2016 · The normal distribution is a common place in natural sciences. The usual explanation is why it happens in measurement errors is through some form of large numbers or central limit …
normal distribution - why n>=30 for central limit theorem to hold ...
May 27, 2021 · From my understanding as size of n increase normal distribution will have smaller standard deviation, this makes sense because using larger sample size will be better at estimating …
t-test when the data population is not normally distributed
May 14, 2020 · I understand that according to CLT the estimator would become normal but, If my population is not normally distributed, let's say it is uniformly distributed. Can I use t-test? let's also …
How are the Error Function and Standard Normal distribution function ...
Well, there's a definition of erf and a definition of the Normal CDF.. The relations, derivable by some routine calculations, are shown as to how to convert between them, and how to convert between …
Why kurtosis of a normal distribution is 3 instead of 0
Dec 3, 2014 · What is meant by the statement that the kurtosis of a normal distribution is 3. Does it mean that on the horizontal line, the value of 3 corresponds to the peak probability, i.e. 3 is the mode …
How to calculate the expected value of a standard normal distribution?
Oct 13, 2015 · Start asking to get answers normal-distribution random-variable expected-value density-function See similar questions with these tags.
Why do we assume that the error is normally distributed?
Due to the Central Limit Theorem, we may assume that there are lots of underlying facts affecting the process and the sum of these individual errors will tend to behave like in a zero mean normal …
How can I convert a lognormal distribution into a normal distribution?
8 I have a sample of data that follows a lognormal distribution. I would like to represent the distribution as a "Gaussian" histogram and overlayed fit (along a logarithmic x-axis) instead of a lognormal …