I have some cells which fluorescence and I can detect their fluorescence. So for each cell I get a number
N that says how much light it emitted.
I also have two kinds of cells
I have measured 1000 cells of type
B each which gives a distribution for each type. I want to know if the mean and standard deviation of these two distributions is the same or not.
In practice (the following numbers are made up the actual measurements contains +25000 cells), I measured 100
A cells 10 times (in total 1000 different cells) and I did similarly for
Each measurement (that includes 100 cells) gives a sample mean and a standard deviation.
Now I want to see if the mean emitted light and the standard deviation of emitted light by cells
B is the same or not so I do a t-test.
My question is if I rearranged my data does it affect the t-test? For example, consider two extremes:
I divide my 1000 measurements for each type of cells into 20 groups of 50 cells instead of 10 groups of 100.
I only consider one group of 1000 cells.
The mean stays the same but the standard deviation changes based on group size. For example, in the second case it is zero!
How should I divide my data into groups for t-test? Or, alternatively, how can I know two distribution have equal mean and standard deviation?