Here is some recent update: Any thoughts?
I have collected a list of experiment result data. I put them into a
table.
There are N rows corresponding to N data points.
For i-th row, it contains data of the form y_i = f(a_i, b_i, c_i, d_i,
e_i, f_i),
where f is a possibly stochastic function, a, b, c, d, e, f are
variables.
Is there a way that I can visualize so many data in a better way?
I can do a histogram of all the y_i's, showing the distribution of
y_i's. That's what I can think of.
But how about those a_i, b_i, c_i, d_i, e_i, and f_i's. Any idea of
how to visualize them? I really want to do a good presentation.
Also, any way of linking y_i and f(a_i, b_i, c_i, d_i, e_i, and f_i's)
all together(both the inputs and outputs)?
losemind wrote:>
> Hi all,
>
> I am doing some experiment studies...
>
> It seems to me that with different combination of 5 parameters, the end
> results ultimately converged to two scalars. That's to say, some
> combinations of the 5 parameters lead to one end result and some other
> combinations of the 5 parameters lead to the other end result (scalar).
>
> I am thinking of this is sort of something like clustering or binary
> classification.
>
> If I could figure out what combinations of the 5 parameters lead to what
> type of end result, in the future, I will be able to predict or classify
> without doing the whole experiment, which is very time consuming...
>
> Could someone give me some recommendations about what might be the best
> stats model for doing this?
>
> And what might be the best stats tool for such task, and are these tools
> available in R?
>
> Thanks a lot!
>
>
>
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