Understanding scale in R

Question

I m trying to understand the definition of scale that R provides  I have data  mydata  that I want to make a heat map with  and there is a VERY strong positive skew  I ve created a heatmap with a dendrogram for both scale mydata  and log my data   and the dendrograms are different for both  Why  What does it mean to scale my data  versus log transform my data  And which would be more appropriate if I want to look at the dendrogram illustrating the relationship between the columns of my data   Thank you for any help  I ve read the definitions but they are whooping over my head

User · Answer

It provides nothing else but a standardization of the data  The values it creates are known under several different names  one of them being z-scores   Z  because the normal distribution is also known as the  Z distribution     More can be found here   http   en wikipedia org wiki Standard score

User · Answer

log simply takes the logarithm  base e  by default  of each element of the vector  scale  with default settings  will calculate the mean and standard deviation of the entire vector  then  scale  each element by those values by subtracting the mean and dividing by the sd   If you use  scale x  scale FALSE   it will only subtract the mean but not divide by the std deviation    Note that this will give you the same values     set seed 1     x  lt - runif 7        Manually scaling     x - mean x     sd x      scale x

User · Answer

This is a late addition but I was looking for information on the scale function myself and though it might help somebody else as well    To modify the response from Ricardo Saporta a little bit  Scaling is not done using standard deviation  at least not in version 3 6 1 of R  I base this on  Becker  R   2018   The new S language  CRC Press   and my own experimentation   X man scaled  lt - X sqrt sum X 2   length X -1   X aut scaled  lt - scale X  center   F    The result of these rows are exactly the same  I show it without centering because of simplicity    I would respond in a comment but did not have enough reputation

User · Answer

I thought I would contribute by providing a concrete example of the practical use of the scale function  Say you have 3 test scores  Math  Science  and English  that you want to compare  Maybe you may even want to generate a composite score based on each of the 3 tests for each observation  Your data could look as as thus   student id  lt - seq 1 10  math  lt - c 502 600 412 358 495 512 410 625 573 522  science  lt - c 95 99 80 82 75 85 80 95 89 86  english  lt - c 25 22 18 15 20 28 15 30 27 18  df  lt - data frame student id math science english    Obviously it would not make sense to compare the means of these 3 scores as the scale of the scores are vastly different  By scaling them however  you have more comparable scoring units   z  lt - scale df  2 4  center TRUE scale TRUE    You could then use these scaled results to create a composite score  For instance  average the values and assign a grade based on the percentiles of this average  Hope this helped   Note  I borrowed this example from the book  R In Action   It s a great book  Would definitely recommend

[r] Understanding `scale` in R

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