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Programme Introduction
In the contemporary era of evidence-based business and management decision-making, the ability to collect, prepare, analyse and interpret data has become an essential research and professional competency. Researchers and academicians increasingly need to move beyond data collection towards selecting appropriate analytical techniques and translating statistical outputs into meaningful insights. Statistical software such as SPSS enables users to undertake these analyses efficiently; however, meaningful application requires both conceptual understanding and hands-on practice.
This three-day online Faculty Development Programme is designed as a hands-on learning experience to strengthen participants' capabilities in statistical data analysis using SPSS. The programme combines conceptual inputs, live demonstrations and guided exercises using research-oriented datasets. Participants will learn the complete analytical process—from understanding data and preparing datasets to conducting exploratory, reliability, factor, inferential, correlation, regression and group-comparison analyses—and interpreting outputs for research and publication-oriented decision-making.
Programme Objectives
Develop a sound understanding of statistical data, research variables and the analytical decision-making process.
Provide hands-on experience in using SPSS for data management, preparation, exploratory analysis and statistical testing.
Enable participants to select and apply appropriate statistical techniques for research questions and hypotheses.
Strengthen participants' ability to interpret SPSS outputs and convert analytical results into meaningful research insights.
Programme Methodology
The FDP will follow a hands-on and experiential approach. Each day will consist of two sessions of two hours each, with guided demonstrations, practical exercises, and discussion. The programme will primarily emphasize application and practice using SPSS and research datasets, supplemented by conceptual explanation and interpretation of results.
Programme Contents (Day-wise)
Day 1: Research Data, SPSS Foundations and Measurement
Session 1: Research Data and SPSS Foundations
Research questions and variables
Types of data and measurement scales
Introduction to the SPSS interface
Data coding and data entry
Import/export of data files
Session 2: Data Preparation and Exploratory Analysis
Data management and data cleaning
Selection and recoding of data
Computing new variables
Handling missing data and outliers
Descriptive statistics, cross-tabulation and data visualisation
Day 2: Reliability, Validity and Statistical Inference
Session 3: Reliability and Factor Analysis
Reliability testing and Cronbach's alpha
Item analysis
Principal Component Analysis (PCA)
Exploratory Factor Analysis (EFA)
KMO, Bartlett's Test, and factor interpretation
Session 4: Statistical Inference and Hypothesis Testing
Introduction to statistical inference
Hypothesis formulation and testing
Confidence intervals and p-values
Parametric tests
Non-parametric tests
Day 3: Relationship Testing and Group Comparisons
Session 5: Correlation and Regression Analysis
Correlation analysis
Simple and multiple regression
Model fit and coefficients
Interpretation of regression output
Session 6: ANOVA and Research Interpretation
One-way ANOVA
Two-way ANOVA
ANCOVA and post-hoc analysis
Interpreting SPSS output
Reporting tables and findings
From statistical output to publication-ready research insights
Prof. Sumeet Kaur
Professor, Operations and Supply Chain Management Area
FORE School of Management, New Delhi
Prof. Sumeet Kaur has over 22 years of research and teaching experience. Her research interests include quantitative techniques, reliability and life testing, business forecasting and managerial decision-making. She has conducted and contributed to programmes and workshops on SPSS, research methods, multivariate data analysis, machine learning and analytics, quantitative techniques, operations excellence and supply chain management.
Prof. Shubhangini Rajput
Assistant Professor, Operations and Supply Chain Management Area
FORE School of Management, New Delhi Prof. Shubhangini Rajput brings expertise in quantitative research and analytical approaches to contemporary management problems. Her academic work spans operations and supply chain management, with research interests that include data-driven decision-making, sustainable and circular supply chains, and analytical approaches to contemporary management challenges.
For more information, please contact Mr. Puneet Garg: +91-98108 75278 | +91-11-41242477 or email us at exed@fsm.ac.in
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Executive Education/MDPs
FORE School of Management has been designing, developing and conducting innovative Executive Education (EE)/ Management Development Programmes (MDPs) for working executives in India for over three decades.
