Descriptive Statistics show an increase but regressions shows no significance - Why? Probably a basic question for many of you:
If I look at my descriptive statistics (looking at mean values as standard deviations are too high) on the impact of different investor types on startup accounting data pre- and post investment (amount of sales, amount of total assets, employee headcount, etc.) than I see a strong increase for all factors after investor provided startups money - no surprise. However, using different multiple regressions we only find significance on the respective dependent variables for some investor types but not all.
Shouldn't I find a significant impact for all investors than?
What's the explanation and why do I even look at the descriptives if the numbers are irrelevant even though some investor types show the highest increase in e.g. sales but the regression analysis show no significant p-value?
Is a univariate regression necessary and advisable?


(looking at mean values as standard deviations are too high)

That should be your clue. The means across types are too noisy. A regression, which more formally gives you the difference in means for a variable, echoes this finding. It may be that some investor types as defined are not meaningfully different from each other. You can bin together types to show your intended variation. Making strong claims as a result of that binning comes close to p-hacking, so I'd recommend at least sharing how/why you constructed your types in your paper/project.
