Statistical technique is a means, not a destination. The most common analytical mistakes begin when researchers choose a method they are comfortable with and then reshape the question to fit it.
Start from the question
Ask what your question actually requires: are you describing, comparing, associating, or modelling relationships between constructs? Descriptive questions call for descriptive statistics; relationships between latent variables may call for structural equation modelling.
Respect your data
Measurement level, sample size and distribution all shape what is defensible. Reliability and validity checks come before hypothesis testing, not after. Software such as SPSS, AMOS and PLS-SEM each suit particular designs — the tool follows the logic of the study.
Above all, analysis should be transparent and reproducible. Interpreting results honestly, including those that do not support your expectations, is part of doing research well.