I have a set of data:
  [http://pastebin.com/KHLKD8XB][1]

which is based on TVC (total viable counts - i.e., numbers of bacteria) from water going into a machine (BM), water taken from the machine (IM) and water taken from a device which is washed in  that machine (Scope).

Whilst the counts are performed on a 200ml sample, results are reported as cfu/100ml, hence you appear to find 1/2 a bacteria in some samples.

    library(ggplot2)
    testscope<-read.csv2("http://pastebin.com/raw.php?i=KHLKD8XB")
    testscope$date<-as.Date(testscope$date) 
    ggplot(data=testscope,aes(x=date, y=tvc, colour=class)) + 
        geom_step()  + facet_grid(class ~ ., scales="free")  + 
        labs(title="Machine TVC versus Scope TVC") + ylab("cfu/100ml")
    

Plotted using ggplot2:

![enter image description here][2]


**My question is:  How can I check whether TVC readings from the Scope are related to TVC readings from the machine ?**

By eye, I can't discern a pattern between the machine level (IM) and the Scope levels.

Note that although I have the BM data, that is not something we are particularly interested in at present - it is IM versus Scope that we need to understand.

EDIT: Note that the dataset uses natural log, not base 10. My mistake.

  [1]: http://pastebin.com/KHLKD8XB
  [2]: https://i.sstatic.net/pksjL.png