How to use Excels (or LibreOffices) T-test (e.g. is it a Welch test, assymetric input matrix…) I'm using Excels T.TEST and LibreOffices TTEST functions, and their documentation is rather lacking, so I figured I ask some things here. I'm not exactly sure if this is the right site, but I can't find something more fitting and I think I have the basics (what goes in what input field) right…

What exactly do they return?
It's not explicitly stated that it is the p-value, but I would assume so. 

What is the difference between Excel and LO, or Excels old TTEST? 
The documentation for Excels old function just states that there is a new one that may provide improved accuracy and whose names better reflect their usage. I would assume for for the standard I'm-clueless-about-statistics-I-just-need-significance situation it should not matter, but I'd rather be safe than sorry.

Is a Type 3 T-test a Welch-test?
According to Wikipedia, I should use said Welch-Test, when my samples standard deviations are not identical, and the documentation says Type 3 is for unequal variance (heteroscedastic). Or is that yet another test?

Can I use strangly formated inputs?
My input sheets are formed rather weird:

    0.8 0.7 0.9 0.8        0.6 0.7 0.8
        0.6 0.9 0.7            0.8 0.9
            0.7 0.8                0.7
                0.6


And I just use the whole A1:D4 and G1:I3 parts, with a lot of empty cells (as in T.TEST=(A1:D4;G1:I3;2;3)). Does that matter or do I have to reformat, for example in simple rows without empty cells?

0.8 0.7 0.9 0.8 0.6 0.9 0.7 0.7 0.8 0.6
0.6 0.7 0.8 0.8 0.9 0.7


and thus T.TEST=(A1:J1;A2:F2;2;3)?
Let me see if I understand. You have $N$ locations. For each location $i\in\{1,\ldots,N\}$, you have $n$ observations (about something). You are trying to see, for a pair $(i,j)$ of locations, if the locations are 'different enough' to treat them separately. That is why you calculated correlation between $i$ and $j$, $\rho_{ij}$. And you are trying to decide whether $\rho_{ij}$ is significantly different from zero and want to use $t$-test for that.

If this is so, then $\rho_{ij}\sqrt{\frac{n-2}{1-\rho_{ij}^{2}}}\equiv t'$ is $t$-distributed with $n-2$ degrees of freedom. Wiki on Pearson correlation coefficient is helpful here. From this getting $p$-value should be easy with the Excel's T.INV/T.INV.2T/T.DIST/T.DIST.2T functions. Namely, plugging $t'$ into T.DIST.2T provides $p$-value for the test which has $\rho_{ij}=0$ as a null and $\rho_{ij}\neq0$ as an alternative.
Let me see if I understand. You have $N$ locations. For each location $i\in\{1,\ldots,N\}$, you have $n$ observations (about something). You are trying to see, for a pair $(i,j)$ of locations, if the locations are 'different enough' to treat them separately. That is why you calculated correlation between $i$ and $j$, $\rho_{ij}$. And you are trying to decide whether $\rho_{ij}$ is significantly different from zero and want to use $t$-test for that.

If this is so, then $\rho_{ij}\sqrt{\frac{n-2}{1-\rho_{ij}^{2}}}\equiv t'$ is $t$-distributed with $n-2$ degrees of freedom. Wiki on Pearson correlation coefficient is helpful here. From this getting $p$-value should be easy with the Excel's T.INV/T.INV.2T/T.DIST/T.DIST.2T functions. Namely, plugging $t'$ into T.DIST.2T provides $p$-value for the test which has $\rho_{ij}=0$ as a null and $\rho_{ij}\neq0$ as an alternative.