Smart strategy in statistics: choosing appropriate test tools for data and hypotheses in quantitative research

Abstract

The selection of appropriate statistical test tools is a major challenge in quantitative research, and errors in their selection can affect the validity and reliability of research results. This study aims to develop a systematic strategy for selecting appropriate statistical test tools based on the type of data and hypotheses used, and provide practical guidance for researchers of various skill levels. The research method used is descriptive research with a qualitative approach, where data is collected through literature studies and case studies on various quantitative studies. The selected test tools were analyzed using content analysis techniques to identify the match with the data characteristics. The results showed that the selection of appropriate test tools improved the accuracy and efficiency of statistical analyses, and the strategy applied helped make it easier for researchers to determine the appropriate statistical test tools through clear groupings based on data types and hypotheses. The implication of this research is the importance of in-depth understanding of the basic assumptions of test tools as well as the application of this strategy to improve the quality and credibility of quantitative research in various disciplines.

Keywords

• statistical testing tools, data types, hypothesis types, quantitative