1.
Exploratory Data Analysis
1.2. EDA Assumptions 1.2.5. Consequences
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Randomness Assumption |
There are four underlying assumptions:
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Consequeces of Non-Randomness |
If the randomness assumption does not hold, then
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Non-Randomness Due to Autocorrelation |
One specific and common type of non-randomness is autocorrelation.
Autocorrelation is the correlation between Yt and
Yt-k, where k is an integer that defines
the lag for the autocorrelation. That is, autocorrelation is a time
dependent non-randomness. 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
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