: Re: How can I mention errors in the data that I received in my thesis? Where to mention it? I received data for data analysis for my Bachelor-Thesis. I still got 4 weeks left to finish the 40

@Odierno164

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Do not publish ANYTHING you know is untrue, or even suspect is untrue.
I am a PhD, a research scientist and former college professor.
You are just in trouble. You cannot publish conclusions that do not hold if the data is in error, you will be publishing a known falsehood.
Your best bet is to rescale the data by some amount, say a factor of 10, or convert mm to inches or vice versa, or Fahrenheit to Centigrade, and see if your same conclusions hold. If the number is arbitrary, try several, like [.25, .5, 2, 5, 10, 50].
If they all give the exact same results, you might be able to say (very early, like at the end of your introduction) that your data was found to have a scaling error of unknown magnitude, but your conclusions held when the data was rescaled by several different magnitudes [.25, .5, 2, 5, 10, 50], thus there is reason to believe the results are scale-invariant.
However, if these experiments do NOT give the same results, you should search for how big or how small the scaling factor can be to get the SAME results, and report that. Test in 10% increments; e.g. [0.10, 0.20, ..., 0.90] for how small, and in larger increments [1.25, 1.50, 2.0, 2.50, 3.0, 3.50, 4.0, 5.0, 7.0, 10.0].
Then you can say (very early) that a scaling error of unknown magnitude was discovered in the data after the completion of the study, but your results hold if the data is rescaled by a factor in [0.25, 5.0]. THAT IS AN EXAMPLE, you will have to find the upper and lower bounds yourself.
If, analytically, your reasoning is relative, (for example, saying "less than 10% of the samples met condition X" or saying "These samples were more than 3 times the magnitude of those samples") then a constant scaling factor will not change the logic of relative statements.
You should examine your paper and see which statements are relative and which are NOT. For example, if you thought temperature was in Fahrenheit and said a temperature of 20 was below freezing (for water), and then discover temperatures are in Centigrade, well 20C is 68F, nowhere near freezing, and that logic and what follows from it just has to be revised or deleted.

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