The effective shear strength is a critical parameter for evaluating ultimate and serviceability limit states of geotechnical structures. To conduct a fully probabilistic assessment or to determine characteristic values according to the second generation of Eurocodes, it is essential to quantify the uncertainty of ground properties due to inherent variability, measurement error, transformation, and statistical uncertainty. However, unlike other ground properties, shear strength parameters are not directly measured, even in laboratory settings. Instead, they are derived from the relationship between shear and normal stresses, making uncertainty analysis nontrivial. This study applies two regression approaches and the extended multivariate approach (EMA) to estimate the effective friction angle for non-cohesive soils. Firstly, an ordinary least squares (OLS) and a Bayesian linear regression (BLR) approach are utilized to quantify the uncertainties inherent in data from direct shear and tri-axial tests from an offshore wind project. Secondly, the EMA is utilized to integrate cone penetration tests (CPT) and shear test data via Bayesian inference. The results are discussed based on characteristic values according to Eurocode 7 (EN 1997-1:2024) highlighting the importance of accurately and precisely estimating mean and uncertainty.