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I have a dictionary of following form:

datetimes = {year : {name : (score1, score2)}} #there are 50+ names/year

So, essentially, I'm trying to get an aggregate picture of how score1 at year_n is correlated with score2 at year_n.

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  • $\begingroup$ which one is your lagged score 1 or 2? $\endgroup$ Commented Mar 21, 2021 at 0:17
  • $\begingroup$ Score1 lags score2. That is, for all of these examples I'm trying to use score1 in 2012 to predict score2 in 2013 (for example). $\endgroup$
    – Jayke
    Commented Mar 21, 2021 at 2:26

1 Answer 1

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An application of a specific correlation formula depends on the data-type (continuous or rank data etc). Given that your data is continuous, you can apply Karl Pearson formula. However, if you're interested interested in cause and effect relationship, you may prefer to use simple regression model.

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