1.
Exploratory Data Analysis
1.3. EDA Techniques 1.3.3. Graphical Techniques: Alphabetic 1.3.3.15. Lag Plot


Lag Plot  
Conclusions 
We can make the conclusions based on the above plot of
the FLICKER.DAT data set.


Discussion 
In the plot above for lag = 1, note how the points tend to cluster
(albeit noisily) along the diagonal. Such clustering
is the lag plot signature of moderate autocorrelation.
If the process were completely random, knowledge of a current observation (say Y_{i1} = 0) would yield virtually no knowledge about the next observation Y_{i}. If the process has moderate autocorrelation, as above, and if Y_{i1} = 0, then the range of possible values for Y_{i} is seen to be restricted to a smaller range (.01 to +.01). This suggests prediction is possible using an autoregressive model. 

Recommended Next Step 
Estimate the parameters for the autoregressive model:
The residual standard deviation for the autoregressive model will be much smaller than the residual standard deviation for the default model
