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here is my scenario:

People record data using sensors, the data is uploaded to a server. Then the users can view their data on a web page. Here is what is in my dataset: - I know how often each user uploaded a record to the server - I know if and how often that user viewed his records on the website

I want to know how often the users viewed their records on the website. Now since not all users have the same life-style and available time to make records and upload them: Would it make sense to standadize the data? If you think yes how would I do that?

Wikipedia tells me the standard scores are calculated by z = (x - mean)/standard deviation. So x is my number of record views on the web page, mean is the mean of the views of all users and standard deviation is ... well the standard deviation of all users' views of their data?

Any help is appreciated. If you think I am completely on the wrong path please tell me =)

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No, if your goal is to know how often users viewed their records, and you already have that data (per first paragraph) then you don't need to do anything and standardization won't help.

If you want to account for things like life-style and available time, then you would need data on the life-style and available time of the people viewing records, or, at least, a sample of them.

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  • $\begingroup$ But what if we assume, the users just recorded as much data as they can in their free time? $\endgroup$
    – Martin
    Sep 11, 2013 at 12:51
  • $\begingroup$ How does that help? $\endgroup$
    – Peter Flom
    Sep 11, 2013 at 13:14
  • $\begingroup$ you are probably right =) $\endgroup$
    – Martin
    Sep 11, 2013 at 13:15

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