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There are many avoidable errors that can occur during analysis, and some of them are:
Selection error: if an inappropriate or insufficient sample is selected, the results may be biased.
Data error: If the data are incomplete, inaccurate, or flawed, the analysis may not be reliable.
Method error: if the wrong analysis methods are used, or if the analysis methods are not performed correctly, the results may be biased.
Interpretation error: If the results are misinterpreted or if they are not contextualized with other relevant information, incorrect conclusions may be drawn.
Bias: If the analysis process is influenced by bias or personal opinion, the results may be skewed.
Missing variables: If important variables are not included in the analysis, the results may not be complete.
Overgeneralization.
Overgeneralization: if the results are applied to a larger population or situation than they actually represent, this can lead to incorrect conclusions.
It is important to be aware of these avoidable errors and to take appropriate steps to minimize or avoid them in order to obtain accurate and reliable results.