Quantitative Techniques: From Hypothesis Testing to Structural Equation Modeling

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Programme Overview:

This 3-day (12-hour) online Faculty Development Programme (FDP) is designed to provide rigorous training in core quantitative techniques widely used in doctoral research, journal publications, and funded research projects. The programme integrates hypothesis testing, predictive modeling, multivariate techniques, and structural modeling with practical demonstrations using SPSS and Jamovi.

Participants will work with varied datasets (for hypothesis testing, predictive modelling, factor analysis, SEM, and perceptual mapping).

The programme adopts a hands-on analytical approach where each statistical technique is demonstrated through datasets, output interpretation, and reporting formats suitable for Scopus-indexed journals.

Programme Objectives

• To equip researchers with the ability to select and execute the correct statistical tests for different data types.
• To master predictive modeling techniques.
• To demystify complex multivariate techniques like Factor Analysis (EFA/CFA) and Structural Equation Modeling (SEM).
• To enable participants to interpret software outputs and report findings.

Programme Pedagogy

The FDP will follow a "Demonstrate-Practice-Interpret" approach:

• Live Software Walkthroughs: Step-by-step guidance on SPSS and Jamovi.
• Case-Based Learning: Using datasets.
• Comparative Analysis: Running the same tests in both softwares to understand the nuances of each.
• Interactive Q&A.

Programme Contents

Day 1: Foundations of Inference & Financial Data Testing

• Hypothesis Testing Framework: Understanding p-values.
  • The "T" Family: One-sample and Independent samples t-test, Paired-samples t-test.
• Analysis of Variance (ANOVA): One-way ANOVA vs. Two-way ANOVA (Testing mean differences across multiple groups).

Day 2: Predictive Modeling & Time-Series

• Correlation & Regression: Simple Linear vs. Multiple Linear Regression.
• Time-Series Analysis: Introduction to Trend analysis and Forecasting.
• Data Pruning: Techniques for outlier detection.

Day 3: Advanced Multivariate Techniques & Marketing Analytics

• Factor Analysis (Reducing Complexity):
  • Exploratory Factor Analysis (EFA) for scale development.
  • Confirmatory Factor Analysis (CFA) to validate existing models.
• Structural Equation Modeling (SEM): Introduction to path analysis and model fit indices.
  • Multi-Dimensional Scaling (MDS): Applications in Perceptual Mapping.
• Mediation and Moderation by PROCESS macro

Who can Attend This Programme

• PhD Scholars: Those in the data analysis or thesis-writing phase.
• Early Career Researchers: Looking to upgrade their toolkit for high-impact research.
• Faculty Members: Especially those teaching Business Research Methods or Analytics.
• Corporate Analysts: Professionals dealing with quantitative data interpretation.

Professional Fee of the Programme

Programme Director: Prof. Rajarshi Debnath

Dr. Rajarshi Debnath has been working as an Assistant Professor in the Marketing Area at FORE School of Management, New Delhi, India. He has also worked as a Visiting Faculty at IMT Ghaziabad. With a PhD from Vinod Gupta School of Management, IIT Kharagpur, he has published papers in ABDC, ABS and Scopus listed journals. He has presented his work at international conferences of repute organised by IIM Ahmedabad, IIM Calcutta, IIM Indore, and IIM Trichy. He has also received financial assistance from IIT Kharagpur to travel abroad to present a research paper at the international conference in the United States. He has reviewed papers for the Journal of Relationship Marketing, Emerging Markets Case Studies, Journal of Advances in Management Research, Journal of Consumer Behaviour and International Journal of System Assurance Engineering and Management. He has edited a book titled Innovation for a Sustainable Future: Selected Cases, by Bloomsbury Publishing. He has also published book chapters in IGI Global and Bloomsbury. He has actively conducted conferences, webinars, workshops, and faculty development programmes. 

For registration/inquiries, please email exed@fsm.ac.in or call at +91 85959 32210 or +91 98108 75278 

 

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