statisticsfuctions
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statisticsfuctions [2015/09/14 06:26] – created mwagner | statisticsfuctions [2024/09/25 06:21] (current) – external edit 127.0.0.1 | ||
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- | ====== RANK-Fuction | + | ====== RANK-Function |
I have been tinkering with LibreOffice Calc and read a book on analysing company data. I came across some interesting statistics functions beyond what most schools teach. Most of them give you a basic introduction on the SUM-Fuction, | I have been tinkering with LibreOffice Calc and read a book on analysing company data. I came across some interesting statistics functions beyond what most schools teach. Most of them give you a basic introduction on the SUM-Fuction, | ||
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I don't know if Postgres has a similar fuction built in but it does have some statistics functions which can be used right on the database-server side. | I don't know if Postgres has a similar fuction built in but it does have some statistics functions which can be used right on the database-server side. | ||
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+ | I am assuming this is also the way amazon.com determines which rank a particular book has in. | ||
Feel free to grab the demo sheet from http:// | Feel free to grab the demo sheet from http:// | ||
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+ | ===== PEARSON-Function ===== | ||
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+ | This fuction determines if a two data sets are interrelated. As an example you might run a company which has different sales outlets (e.g. Apple stores) which have a certain size and produce a certain amount of turnover. You might as yourself if the size of the store and the turnover are interrelated. In short words: If I create bigger stores, will they produce more turnover taking these two factors into account? | ||
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+ | The Syntax is quite simple: | ||
+ | **=PEARSON(Matrix1; | ||
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+ | Again, I have set up a demo sheet at http:// |
statisticsfuctions.1442211984.txt.gz · Last modified: 2024/09/25 06:19 (external edit)