# Regression of 6 input parameters

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,

• This question is way too broad. – Peter Feb 8 '17 at 21:29
• how can I modify it? – The Fire Guy Feb 8 '17 at 21:30
• 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. – Peter Feb 8 '17 at 21:30
• 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. – The Fire Guy Feb 8 '17 at 21:32
• @TheFireGuy Calculate the covariance matrix & then calculate its largest eigen-vector ... sorry I did not answer sooner (I had to go & have my bath !) – Donald Splutterwit Feb 8 '17 at 23:23