Paper Contents
Abstract
The purpose of this study is to conduct a comparative analysis of statistical results generated by four of the most widely used tools in data analysis: Python, R, SPSS, and Excel. The paper aims to examine the similarities and differences between these platforms in terms of accuracy, flexibility, processing time, and methodological approach. In the framework of the research, the data were processed using common statistical techniques such as descriptive analysis, inferential tests (t-test, ANOVA), as well as visualization methods. The results showed that, although all four platforms reach similar conclusions, there are significant differences in the level of usability, execution speed, and advanced analysis capabilities. Python and R offer greater flexibility and opportunities for sophisticated analysis, while SPSS offers a friendly interface and standardized results for social science users. Excel, although limited in complex analysis, remains useful for quick calculations and basic visualizations. This study provides a practical and theoretical contribution to choosing the most appropriate tool for data analysis depending on the research purpose, user profile, and available resources.
Copyright
Copyright © 2025 Senad Orhani. This is an open access article distributed under the Creative Commons Attribution License.
