Compare two groups? Find what drives an outcome? Spot a trend? The question decides the statistics: get this wrong and everything downstream is wrong too. More are in build.
That is the actual report this analysis produces, not a mock-up. Every analysis on this page delivers the same shape of output on your own data.
Every analysis classified under this question.
Should I accept this lot?
Which rows do not fit the usual pattern, including in combination, and what makes each stand out.
Do these numbers look fabricated or manipulated?
Which measures rise and fall together, how strongly, and in which direction, with every pair tested.
Every column in your file: its type, what is missing, how its numbers are spread. Plus the fixes worth making before you analyse it.
Is my data normal, and are there outliers?
What distribution does my data follow? Fit and compare candidate distributions with goodness-of-fit tests.
How reliable are these ratings across raters or repeat measurements?
How bad is my missing data and does it bias my results? Missingness patterns, MCAR checks, imputation impact.
Do your survey items hold together as one scale?
How much variance is the measurement system itself.
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