1.
Exploratory Data Analysis
1.2. EDA Assumptions 1.2.5. Consequences


Randomness Assumption 
There are four underlying assumptions:


Consequeces of NonRandomness 
If the randomness assumption does not hold, then


NonRandomness Due to Autocorrelation 
One specific and common type of nonrandomness is autocorrelation.
Autocorrelation is the correlation between Y_{t} and
Y_{tk}, where k is an integer that defines
the lag for the autocorrelation. That is, autocorrelation is a time
dependent nonrandomness. This means that the value of the current
point is highly dependent on the previous point if k = 1
(or k points ago if k is not 1). Autocorrelation is
typically detected via an
autocorrelation plot or a
lag plot.
If the data are not random due to autocorrelation, then
