by MAPK
Last Updated August 14, 2019 17:19 PM

I was trying to analyze two groups of samples for multiple variables. I first used Boruta (random forest analysis) test to determine the importance of variables in my data.
`Boruta analysis`

Boruta test identified `Actinomycetes%`

to be the only (significantly) important variable. Then I did `t.test`

and `regression analysis`

on the variable Actinomycetes% and found them to be not significant. Also, the p-values I got from t.test is ~0.14 and regression analsysis is ~0.9. So, I would like to ask the community these two questions:

- Why does Boruta test show
`Actinomycetes%`

to be significant and not by t.test and regression analsysis? - Why are the p-values from t.test (0.19) substantially smaller than the p-value from regression analysis(0.9)?

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