White noise in time series

What is a White Noise Time Series? A time series may be white noise. A time series is white noise if the variables are independent and identically distributed with a mean of zero. This means that all variables have the same variance (sigma^2) and each value has a zero correlation with all other values in the series.

1. What is white noise in data?
2. Is white noise time series stationary?
3. Does white noise mean autocorrelation?

What is white noise in data?

White Noise is a random signal with equal intensities at every frequency and is often defined in statistics as a signal whose samples are a sequence of unrelated, random variables with no mean and limited variance. In some cases, it may be required that the samples are independent and have identical probabilities.

Is white noise time series stationary?

Thus, time series with trends, or with seasonality, are not stationary — the trend and seasonality will affect the value of the time series at different times. On the other hand, a white noise series is stationary — it does not matter when you observe it, it should look much the same at any point in time.

Does white noise mean autocorrelation?

A white noise process has an autocorrelation function of zero at all lags except a value of unity at lag zero, to indicate that the process is completely uncorrelated.