Autocorrelation is the correlation between values of a time series and previous values of the same series. Autocorrelation plots check randomness by computing correlations at varying time lags, with random data showing correlations near zero at all lags. The autocorrelation plots of 4 heating system time series can reveal if data is random, related between observations, white noise, sinusoidal or autoregressive, helping understand relationships between data points. Autocorrelation plots are analyzed for 4 heating system time series to check randomness and relationships between values over time.