Adding two (or more) means and calculating the new standard …
There are a load of discussions online about adding means and recalculating the standard deviation, but on ...
How to 'sum' a standard deviation? - Cross Validated
If you add the "local" variances together, it will be very small compare to the "global" variance. You cannot predict the variance of the year using variance of 2 half year. So, in the accepted …
mathematical statistics - Will the mean of a set of means always …
2015年1月13日 · So what we see is that you certainly can calculate the mean of the means, but the mean of the means and the mean of all the raw data don't match. We can also try a …
Can I take a mean of a set of means? - Cross Validated
2018年1月18日 · So as you can see, the actual mean of the whole sample is a weighted average of the sample means of the subgroups (where each weight is proportionate to the size of the …
Is it possible to find the combined standard deviation?
I had the same problem: having the standard deviation, means and sizes of several subsets with empty intersection, compute the standard deviation of the union of those subsets. I like the …
Assigning class labels to k-means clusters - Cross Validated
2013年3月6日 · In the case of k-means you compute the euclidean distance between each observation (data point) and each cluster mean (centroid) and assign the observations to the …
How to combine sample means and sample variances?
I read about pooled variance, but this is not depending on the means of the subsets and can't therefore possibly be true, since the spacing of the two "subgaussians" is obviously of …
Multiplying means and calculating variance - Cross Validated
2017年8月1日 · I have multiplied together two means and now want to calculate the overall standard deviation. The two means and standard deviation are here: 13.7 +/- 12.7 (1SD) and …
Combining two means and SDs of one group [duplicate]
2018年12月30日 · $\begingroup$ Take the 84 data points and ignore the time. calculate the mean and SD for the 84 combined. Let me assume, for example, you want average weight and …
What is the relation between k-means clustering and PCA?
2015年11月24日 · K-means is a least-squares optimization problem, so is PCA. k-means tries to find the least-squares partition of the data. PCA finds the least-squares cluster membership …