[R] How to evaluate impact of factors on parameters

[lionel sicot]

Hello,
One of my colleagues sent me a csv file with 12 columns and a lot of rows. Column1 to Column10 are factors with 2 to 6 levels. Column11 and Column12 are experimental results.I'm a bit lost with all these data.
I would like- to determine which factors have the most impact, and in which way, on Column10 (which has to be as high as possible) while Column 11, at the same time, has to be as low as possible (I hope it is clear for at least one of you ...).- to find a nice way to plot trends as there are several factors.

Below is a small data.frame from the SixSigma package (4 columns of factors and 2 columns of values). I don't know if it can help you to show me how to "play" with my data.If not, a package name or a tutorial can also be hepful.
Thanks in advance,Ptit Bleu.
df_test<-read.table(text="pc.col pc.filler pc.batch pc.op pc.volume pc.densityC 1 1 A 16.7533110462178 1.25341925113923C 2 1 B 18.0143546656987 1.11243453179479C 3 1 C 15.6448655396281 1.14110454507519C 1 1 D 18.0281678426422 1.09177192905336C 2 2 A 13.7831255488576 1.1465474843639C 3 2 B 16.758396178001 1.12333920013556C 1 2 C 14.6938147409883 1.34554594406146C 2 2 D 15.1974804312962 1.18442400447752C 3 3 A 14.2077591655389 1.45756680703941C 1 3 B 15.9579675459773 1.18602487934004C 2 3 C 18.1500426178447 1.27641549258776C 3 3 D 14.2297691617968 1.28052785172529B 1 4 A 16.8646535945654 1.30119623444795B 2 4 B 14.2798441018389 1.11228530554194B 3 4 C 16.1341256681412 1.27060268503477B 1 4 D 15.9241734353476 1.34131613229472B 2 5 A 16.8583005443759 1.19909272287678B 3 5 B 16.3449003481023 1.19954395487512B 1 5 C 15.4175473098922 1.54100836814473B 2 5 D 16.7861703759254 1.31241568978863B 3 6 A 15.3079007135867 1.14210653222791B 1 6 B 14.8169564636873 1.21694093094929B 2 6 C 17.2688507060631 1.2603211001675B 3 6 D 15.6874484539888 1.32986554107345", header=T)


	[[alternative HTML version deleted]]