Articles
| Open Access |
https://doi.org/10.37547/ijp/Volume05Issue06-117
Implementation of Statistical Methods in SPSS Software
Abstract
The integration of statistical methods into data analysis is essential across scientific disciplines, ensuring rigor and validity in empirical research. Among the various software tools available for statistical processing, IBM’s Statistical Package for the Social Sciences (SPSS) has become one of the most widely adopted platforms due to its user-friendly interface and robust analytical capabilities. This article explores the implementation of key statistical methods in SPSS software, analyzing its theoretical foundations, practical applications, and implications for empirical research. The study details the core functions and methodological features of SPSS, discusses challenges and advantages of its use, and examines the impact of SPSS-enabled analyses on research reliability and reproducibility. Real-world examples from diverse fields are considered to illustrate the versatility and depth of SPSS’s statistical toolset. The discussion highlights considerations for researchers in selecting appropriate statistical techniques and optimizing workflow within SPSS. The article concludes by reflecting on the software’s role in modern data analysis and the future trajectory of statistical computing.
Keywords
SPSS, statistical analysis, data processing
References
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