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I have a set of data that contains 6 inputs and 1 output (about 500 rows). Basically, I'm trying to figure out the complex relationship between the 6 inputs (say different component of concrete mix, i.e. sand, aggregate, water etc.) in order to predict the strength of concrete (output).The data was collected through a number of experiments. I'm trying to figure out the relationship between them. For instance, if you reduce water volume, the strength decreases.

I was wondering if anyone can provide me with some tips or software (and/or tools) that can help me.

Thanks,

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    This question is way too broad. – 2017-02-08
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    how can I modify it? – 2017-02-08
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    Give us more information (kind of the datas, how they are related etc.) You only mentioned that $6$ inputs influence the data. But without knowing at least approximately how, it is impossible to find a suitable model. – 2017-02-08
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    The data was collected through a number of experiments. I'm trying to figure out the relationship between them. For instance, if you reduce water volume, the strength decreases. – 2017-02-08
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    Exact such details is what you should add to the question. – 2017-02-08
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    Thanks! I have updated the question. – 2017-02-08
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    Do a principle component analysis on the six variables & then use the eigenvector corresponding to the largest eigenvalue. Then treat it as 1-1 regression problem – 2017-02-08
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    @DonaldSplutterwit how can I do that? Could you please elaborate a little more. – 2017-02-08
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    @TheFireGuy Calculate the covariance matrix & then calculate its largest eigen-vector ... sorry I did not answer sooner (I had to go & have my bath !) – 2017-02-08

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