Use of Statistical Methods in Bachelor and Master Theses: Data Requirements, Sample Sizes, and Practical Guidance with Methods and Examples

This article provides a structured and practical overview of the use of statistical methods in Bachelor’s and Master’s theses, with a particular focus on data sources, sample size requirements, and methodological decision making. It addresses common challenges faced by students, especially within limited research time frames, by linking methodological rigor with feasibility. The paper distinguishes between three primary data sources: interview based data, questionnaire based data, and secondary data, outlining their characteristics, advantages, and limitations. Clear guidelines for sample sizes are presented for both qualitative and quantitative research, emphasizing concepts such as data saturation and statistical power. In addition, the article explains key statistical methods, including descriptive statistics, correlation analysis, regression analysis, t tests, ANOVA, and qualitative content analysis, supported by practical examples. The importance of data quality is highlighted through the criteria of validity, reliability, and objectivity. Furthermore, the paper offers guidance on selecting appropriate methods based on research objectives and identifies common mistakes to avoid. Overall, the article aims to support students in conducting scientifically sound, methodologically appropriate, and practically feasible empirical research.