Why Apply SPSS, SmartPLS and AMOS: An Essential Quantitative Data Analysis Tool for Business and Social Science Research Investigations

Bipul Sarker (), Debobrota Kumar Sarker, Shompa Rani Shaha, Deepongkor Saha and Saurav Sarker
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Debobrota Kumar Sarker: Managing Director & CEO, SouthAsia Research & Corporate Advisory Ltd, Dhaka-1000, Bangladesh
Shompa Rani Shaha: Investment Specialist, SouthAsia Research & Corporate Advisory Ltd, Dhaka-1000, Bangladesh
Deepongkor Saha: Technical Advisor, SouthAsia Research & Corporate Advisory Ltd, Dhaka-1000, Bangladesh
Saurav Sarker: Technical Advisor, SouthAsia Research & Corporate Advisory Ltd, Dhaka-1000, Bangladesh

International Journal of Research and Innovation in Social Science, 2024, vol. 8, issue 9, 2688-2699

Abstract: In the realm of business and social science research, selecting the right quantitative data analysis tool is pivotal for deriving actionable insights and validating hypotheses. This study were used a qualitative comparison and contrast methodology. The objective is to highlight the benefits of each tool and its appropriate uses in social science and commercial research. SPSS, SmartPLS, and AMOS are three prominent tools each offering distinct advantages tailored to various research needs. SPSS (Statistical Package for the Social Sciences) is widely recognized for its comprehensive range of statistical procedures and user-friendly interface, making it ideal for performing detailed descriptive and inferential analyses. SmartPLS (Partial Least Squares Structural Equation Modeling) specializes in variance-based SEM, providing robust capabilities for exploratory research and predictive modeling with complex datasets. Its focus on prediction and theory development is particularly beneficial for handling large and intricate models. AMOS (Analysis of Moment Structures), on the other hand, excels in covariance-based SEM, offering extensive tools for confirmatory factor analysis and structural modeling. Its graphical interface and model fit indices facilitate detailed model validation and hypothesis testing. Each software has its strengths and limitations, making them essential tools for addressing different aspects of quantitative research. Understanding their unique capabilities allows researchers to select the most appropriate tool for their specific analytical requirements.

Date: 2024
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