We support a wide array of methods including descriptive statistics, regression analysis, ANOVA, Structural Equation Modelling (SEM), and time-series forecasting.

SPSS is highly recommended for survey-based social science research where you need quick, reliable cross-tabulations, ANOVA, and standard regression models without writing code.

R and Python are ideal for handling massive datasets, developing complex machine learning models, conducting advanced econometric forecasting, or creating highly customized data visualizations.

Statistical analysis typically focuses on exploring data and testing specific hypotheses (e.g., t-tests). Statistical modelling involves building predictive or explanatory mathematical equations (like regressions) to understand the deeper relationships between variables.

Yes, we provide detailed written interpretations of complex outputs, translating software tables into academic insights that directly answer your research questions.