Research Methodology 2.0

Event Name: Research Methodology 2.0 Event Date: 05-13 December 2022
Faculty Coordinators: Dr. Fehmina Khalique Event Timings:2:00 PM-5:00 PM
Mode: Online Number of Participants:80
Guest Speakers:Dr Halal Faisal, Dr Masood Siddique, Dr Saurabh Agarwal, Dr Raja Shankaran Venue: Lloyd Business School

Objectives

  • To enhance participants' research skills by providing in-depth training in basic and advanced statistical analysis techniques using SPSS and R.
  • To familiarize participants with modern research tools and techniques, including SPSS for statistical analysis and R for advanced data analytics.
  • To develop participants' expertise in both bivariate and multivariate analysis, enabling them to conduct robust and comprehensive research.
  • To introduce participants to advanced analytical methods such as bibliometric analysis and meta-analysis, broadening their understanding of research review and evaluation techniques.
  • To promote the practical application of research methodologies by engaging participants in hands-on sessions and real-world scenarios, enhancing their ability to apply theoretical knowledge in practice.

The Research Cell of Lloyd Business School conducted the 7-day Online Faculty Development Program (FDP) on “Research Methodology 2.0” from December 5 to December 13, 2022. The program attracted a diverse audience of 80 participants, including national and international academics, students, research scholars, and faculty members. This report summarises the key activities and sessions held during the program.

Day 01: Introduction to SPSS

On December 5, 2022, the FDP commenced with Dr. Hala Faisal, Dean of the Department of Economics at the Lebanese University, serving as the resource person. Dr. Fehmina Khalique, Associate Professor at Lloyd Business School, introduced the workshop, and Dr. Vandana Arora Sethi, Chief Strategy Officer at Lloyd Group of Institutions, delivered the welcome address.

The session covered various aspects of SPSS software, including:

  • Data entry
  • Data sorting and transformation
  • Descriptive statistics
  • Graphical display
  • Correlation and regression analysis

Dr. Faisal also provided insights into data manipulation techniques.

Days 02 and 03: Bivariate Analysis Using SPSS

Dr. Masood H. Siddiqui, Professor and Head of the Department of Statistics at the University of Lucknow, led the sessions on bivariate analysis using SPSS. The topics covered included:

  • Exploratory data analysis
  • Significance testing
  • Statistical inference
  • Parametric testing

Day 3 focused on:

  • Hypothesis testing
  • Correlation analysis
  • Regression analysis

Dr. Siddiqui’s sessions offered an in-depth understanding of research methodology and its applications.

Days 04 and 05: Multivariate Analysis Using Open-Source R

Dr. Saurabh Agarwal, Professor of Machine Learning and Data Analytics at HBTI Kanpur, conducted sessions on multivariate analysis using open-source R. Dr Agarwal, an alumnus of IIT Kanpur and IIT Delhi, covered:

  • Multiple Regression
  • Logistic Regression
  • Binary and Multinomial Regression
  • Linear Discriminant Analysis
  • Ordinal Regression

The sessions provided comprehensive insights into advanced statistical techniques and their practical applications.

Days 06 and 07: Bibliometric Analysis and Meta-Analysis

Dr. Raja Sankaran, Professor at CMS Business School, Jain (Deemed-to-be University), led the bibliometric analysis and meta-analysis workshop. He emphasized the importance of systematic literature reviews and introduced various tools.

The program concluded with an engaging online quiz with enthusiastic participation from all registered attendees. Dr. Ruchi Garg delivered the vote of thanks, acknowledging the contributions of all speakers and participants.

Learning Outcome

  • Participants gained hands-on experience with SPSS, including data entry, sorting, transformation, and conducting various statistical analyses such as descriptive statistics, correlation, and regression.
  • Attendees developed a deep understanding of bivariate analysis techniques, including exploratory data analysis, significance testing, hypothesis testing, and parametric testing using SPSS.
  • Participants acquired advanced skills in multivariate analysis using open-source R, including multiple regression, logistic regression, and other complex statistical techniques such as linear discriminant analysis and ordinal regression