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I am trying to understand how polinomial interpolation works and how I should implement it on Scilab. A friend suggested to see covid-19 day-by-day new infected and to compare the polinomial interpolation with the real data. I understood how it works in the theorical aspect, but I didn't understand how to do it in practice. I don't have any instrument and my friends are using Scilab, so I think I'll do it too. So I have Italian open data about covid19, but how can I get them together and work on them? Has anybody done the same thing so far? Can you link mee examples please? Thanks

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    $\begingroup$ Hi there. MathOverflow is only for questions about research-level mathematics. As this is at a more elementary level, your question would be better for math.stackexchange.com, stats.stackexchange.com, or a Scilab-specific forum. $\endgroup$ – Nate Eldredge May 23 at 12:17
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    $\begingroup$ Hi @NateEldredge, thank you very much for your advise! In effect, I feel lost also from this point of view... I'm still a beginner at stackexchange :) $\endgroup$ – hellomynameisA May 23 at 12:46
  • $\begingroup$ Since this is a statistical problem give cran.r-project.org a try. $\endgroup$ – Dieter Kadelka May 23 at 15:12
  • $\begingroup$ Hi @DieterKadelka! Why is it statistical? I am studying both numerical analysis, data science (and R) and statistics, but I thought it was more a numerical analysis "problem" to solve. Can you explain your point of view please? $\endgroup$ – hellomynameisA May 23 at 15:17
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    $\begingroup$ The reason why I think it's not a problem of polynomial interpolation is that this doesn't make any sense with more or less random data. Scilab, Matlab or Octave have tools that can do polynomial interpolation very well, but the result will be more or less useless. As a numerical analyst you should know that the polynomial interpolation is exakt at the points given but between the polynom behaves quite irregular. Linear models in statistics are a (not the) tool you can choose. R has many variants. With these tools the approximation is also good "between the points". $\endgroup$ – Dieter Kadelka May 23 at 16:05

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