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Hello everyone! Sometimes it is necessary to do some transofrmations in the time series, like logarithmic transformations, differentiation, etc. So when we are going to make the forecast, we use the transformed data. The question is: do we need to do some reverse process on the data after the...

Data in a data set need to be normally distributed for Linear Regression? If so, both independent and dependent variables need to be normally distributed? Tank you!

When I execute a shapiro test on R, i get the folowing result: W = 0.98612, p-value = 0.3814 All documentation that i read, talk about p-value, but what is the meaning of the W (W = 0.98612 in this case) Tanks in advance!

I have a small time series, from which I apply a hypothesis test that informs me that it is not stationary. However, as much as I apply differentiation several times, it is still not stationary. Can this have to do with the amount of data (little data)? Or what else could be the reason? Tank you

Hello folks I am trying to understand how to set the parameters to fit an Arima model: (p,d,q) d seems quite clear. But what about p (AR) and d (MA)? I saw an exam that looks at the ACF for MA (q) and PACF for AR (p) If, for example, there is autocorrelation in lag 7 of the ACF and PACF, it...

The residual concept in regression is clear to me. But, when looking a time series, I was a bit confused: Quote from Forecasting: principles and practice – Rob J Hyndman, George Athanasopoulos When we make a time series forecast, we estimate each point in the future, there is no better fit...

I'm a bit confused about autocorrelation. I understood that I should not expect my residuals to be autocorrelated. But what about the time series data itself, should I expect to find autocorrelation in them? Tank you in advance.