In the era of precision cosmology, establishing the correct magnitude of statistical errors in cosmological parameters is of crucial importance. However, widely used approximations in galaxy surveys analyses can lead to parameter uncertainties that are grossly mis-estimated. These approximations can be introduced at three different levels: in the form of the likelihood, in the theoretical modelling of the observable and in the numerical computation of the observable. Their consequences are important both in data analysis through e.g., Markov Chain Monte Carlo parameter inference, and when survey instrument and strategy are designed and their constraining power on cosmological parameters is forecasted, for instance using Fisher matrix analyses. In this work, considering the galaxy angular power spectrum as the target observable, we report one example for each of such three categories and derive their impact on the estimated parameters uncertainties and degeneracies. We show that there are cases where these commonly used approximations lead, perhaps counterintuitively, to unacceptably large mis-estimates of parameters errors and correlations. Furthermore, we stress how these approximations might even spoil the benefits of the nascent multi-tracer and multi-messenger cosmology. Hence we recommend that the type of analysis presented here should be repeated for every approximation adopted in survey design or data analysis, to quantify how it may affect the results. To this aim, we have developed Multi CLASS, a new extension of CLASS that includes the angular power spectrum for multiple (galaxy and other tracers such as gravitational waves) populations. The public release of Multi CLASS is associated with this paper.