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Learn about Jupyter Notebooks - the easiest way to share, manage, and view Python code as text, tables, and graphs - See below for details I don't know if I get the wrong impression that you are somehow trying to confuse or mislead the community. Or you are somehow pretending to do so to mask the true intention of your question. As you can see, you write the following in your question: I want to do some basic stats about it, mean, standard deviation, and any other metrics I should know about. A person with the right to ask and answer questions on this site (with the capability to edit your question as required) will decide how to interpret the following: Should I only use the first sample size and the first kind of data I have? Or do I have to use all the sample sizes and data types I have? I'll translate that as: Would you consider the two samples to be of different distribution? Should I use both samples in my analysis? And my interpretation is that you would like to know the answer to this question, since that is stated in your question: How much do I gain in accuracy if I use more than one sample size and more than one data type? The answer to that question is in your question: As I have a lot of different data types, what is the best way to do the analysis? My interpretation is that you are asking the question How should I use the data? That question is not a good fit for the site (you would need to ask a question like that on a maths site) and thus cannot be answered. There are things one could do to make your question more clear and useful, such as: Reduce the scope to just one of the four things listed in the title. Change the title to something like "I want to find a correlation between X and Y, but the problem is that there is some sort of systematic bias" I would note, however, that "To answer this question, you need to analyze the data and make some assumptions about the underlying distributions of the data. In many real-world cases, we don't have data to test hypotheses; and in cases where we have data, we don't have that much data." means that you are asking a question that can not be answered in an "eleg

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