Difference Between 'Raw Data' and 'Diff Raw Data'

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Raw data refers to unprocessed information directly collected from sources, while 'Diff Raw Data' represents the differences between consecutive data points in the raw dataset, highlighting changes over time or between observations. The discussion also touches on log-transformed data, where 'Diff Log Data' similarly indicates the differences between consecutive log-transformed values. The user expresses confusion about how 'Diff Data' is derived from the original graphs, seeking clarity on the calculation process. Ultimately, the conversation emphasizes the importance of understanding data transformations and their implications for analysis.
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Difference Between 'Raw Data' and 'Difference Raw Data'

I have a whole bunch of information and it's plotted on a graph.

The first graph is the raw data plotted, no transformations done to the data, it is raw.
The second graph is the same data but it says 'Diff Raw Data'
The second graph looks similar but you can tell it's different

The same applies for another graph of the data, but it's the log of the points, this graph is just the log of the points, no alterations
The second graph is the 'Diff Log Data'
again, the second graph looks simliar but you can tell it's different

Does anyone know how what 'Diff Data' means and how they get it from the first graph? The explanation doesn't refer to how they got the second graphs of Diff Data and I am just confused and have understanding of this.

Thank You
 
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I think you are being to vague. You never mention what you are even using to graph with.
 
I figured it out. yea, I was being to vague. Thanks.
 
The standard _A " operator" maps a Null Hypothesis Ho into a decision set { Do not reject:=1 and reject :=0}. In this sense ( HA)_A , makes no sense. Since H0, HA aren't exhaustive, can we find an alternative operator, _A' , so that ( H_A)_A' makes sense? Isn't Pearson Neyman related to this? Hope I'm making sense. Edit: I was motivated by a superficial similarity of the idea with double transposition of matrices M, with ## (M^{T})^{T}=M##, and just wanted to see if it made sense to talk...

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