A useful tool to evaluate your data before you begin your analysis is the summary() function, which provides a summary of the non-parametric descriptors of a sample, as follows:
> summary(probeA) Min. 1st Qu. Median Mean 3rd Qu. Max. 4.211 4.645 4.774 4.774 4.892 5.231
You can also get a summary for each column of the matrix using the summary() function, as follows:
> summary(MLLpartner.mx) #output truncated GSM487973 GSM487972 GSM487971 Min. : 2.112 Min. : 1.805 Min. : 1.994 1st Qu.: 3.412 1st Qu.: 3.410 1st Qu.: 3.411 Median : 4.736 Median : 4.745 Median : 4.731 Mean : 5.342 Mean : 5.346 Mean : 5.355 3rd Qu.: 6.870 3rd Qu.: 6.851 3rd Qu.: 6.933 Max. :14.449 Max. :14.453 Max. :14.406
We can also get this information by calling the individual functions used to determine these parameters, namely the mean, median, min, max, and quantile functions, as follows:
>...