Frequently Asked Questions

What is White Noise in Time Series?

White noise is a special type of time series where data doesn’t follow any pattern. It is a sequence of random data where every value has a time series associated with it.

Since no pattern is followed, it is difficult to predict white noise.

For data to be white noise, it should follow the below conditions:

  • Constant Mean = 0
  • Constant Standard Deviation
  • No Autocorrelation

Autocorrelation is the measure of how correlated a series is with the past version of itself. No autocorrelation means there is no clear correlation between the present and past values of a series.

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