Autocorrelation and partial autocorrelation functions

Figure 2.12 shows the autocorrelation and partial autocorrelation of rainfall data. These are the plots used to display the correlated data with the significant level. In the figure, the data are correlated within the boundary level with 95% confidence interval significant level. Partial autocorrelation is the relationship between the observed data which has applied time series and observed values of pre-​level of time series. So, in this plot most of the data lie between the significance boundaries compared with the ACF. The term lag is used in both ACF and PACF plots which is time units of t and h, where h is quantity value of covariance.