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I am doing some explorative work on two large datasets. One from 2001 and one from 2018. The dataset consists of measured soil-parameters and it contains lots of zero's.

From the transformations done in 2002 on the 2001 dataset, I have some notes written on the sideline of a LOGtransform graph: 'dataset contains '0'-values, 2 is highest number in column, so LOG(data+0.1)'.

The result of this transformation: enter image description here

My Question: Where does this 0.1 come from in relation to the 2 (highest number in column, dataset)? What is this transformation called and what is the idea behind this kind of log transform?

I have the same skewness in my 2018 dataset, but the LOG(data+0,1) does't work as well. Also, can I compare the two with Repeated Measures ANOVA when the two log transformations have different numbers added to the data?

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  • $\begingroup$ Why do you want to take the logs? What exactly is the problem? $\endgroup$
    – Tim
    Commented Apr 4, 2019 at 14:13
  • $\begingroup$ I want the data to have a (close to) normal distribution for parametric variance testing of the means. i.e. did soil parameters change significantly over years. $\endgroup$
    – Stevestingray
    Commented Apr 4, 2019 at 14:15
  • $\begingroup$ Also the following are worth checking stats.stackexchange.com/questions/30728/… and stats.stackexchange.com/questions/18844/… and stats.stackexchange.com/questions/298/… $\endgroup$
    – Tim
    Commented Apr 4, 2019 at 14:18
  • $\begingroup$ This is answered in here: stats.stackexchange.com/questions/30728/… $\endgroup$
    – Tim
    Commented Apr 4, 2019 at 14:34
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    $\begingroup$ As far as the name goes, John Tukey called this the "started log." However, I don't think that has gained much popularity, so I would be reluctant to use this term without first defining it. $\endgroup$
    – whuber ♦
    Commented Apr 4, 2019 at 20:55

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