Department of Statistics
“Statistics Beyond Numbers – Empowering All Domains Through Data Mastery.”
Introduction
The Department of Statistics at Aspire Tech Park is not just for statistics majors, it is a core skill hub designed for students, scholars, and professionals from any academic discipline who wish to apply statistical tools effectively in research, industry, or data-driven careers.
Aspire’s vision to bridge the gap between theory and real-world skills is reflected here by offering application-based statistical training across life sciences, physical sciences, social sciences, engineering, pharmacy, and business domains. Each program focuses on hands-on exposure to software, data interpretation, and research-ready analysis techniques that learners can apply in projects, publications, and placements.
This department is foundational for those pursuing research careers and for job roles where data analysis, scientific reasoning, and decision-making are essential.
Currently Active
Foundational and software-based courses in Excel, R, and SPSS are open for registration.
Courses Under Validation
Advanced modules using Python, SAS, and domain-specific case studies are being finalized by experts and academic partners.
Foundational Webinars
- Why Every Researcher Needs Statistics
- From Data to Decision: Statistical Thinking Across Fields
- Career Roles for Statistically-Skilled Professionals
- Introduction to Scientific Publishing with Statistical Validation
- Errors, Bias, and Validity: The Ethics of Data Interpretation
Online Hands-on Training Workshops
- Excel for Research Data Handling and Basic Statistical Tests
- Introduction to SPSS: Descriptive Stats, t-Test, ANOVA, Chi-Square
- Getting Started with R: Data Cleaning and Graphing
- GraphPad Prism for Life Sciences & Clinical Research
- Python for Beginners in Statistical Computing
Offline Hands-on Training Workshops
- Real-Time Data Collection and Analysis Projects (via partner hubs)
- Multivariate Analysis using SPSS and R
- Case-Control & Survey-Based Study Design with Analysis
- Domain-Specific Labs (e.g., Agricultural Stats, Pharma Stats, Social Science Data)
- Experimental Design, Randomization, and Result Reporting
Certification Courses
Basic Level
- Introduction to Applied Statistics for All Domains
- Statistical Software Skills: Excel, SPSS, and GraphPad
- Data Cleaning, Visualization, and Interpretation
Advanced Level
- Advanced R Programming for Statistical Modeling
- Statistical Research Design and Analysis using SPSS & Python
- SAS for Industrial and Pharmaceutical Data Analytics
- Biostatistics and Clinical Trial Analysis
- Machine Learning Basics with Statistical Foundations
Internships (Online & Offline)
- Online Internship: Data Analysis Projects using SPSS & R
- Offline Internship: Statistical Analysis in Research & Publication
- Domain Internship: Use of Stats in Environmental, Health, or Social Projects
- Mini Project Internship: Complete Data Pipeline – From Collection to Visualization
Outcomes
- Gain software proficiency in SPSS, R, Python, Excel, GraphPad, SAS
- Learn how to design, analyze, and report experiments or surveys
- Develop critical reasoning, pattern recognition, and validation strategies
- Build a strong analytical profile suitable for research, publishing, and industry
- Receive domain-relevant feedback from experts for every project
Target Job Placement Sectors
- Data Analysis and Business Intelligence Firms
- Clinical Research Organizations and Pharma Analytics
- Research Assistant and Project Analyst Roles in Academia
- NGOs and Survey Agencies (Impact Studies, Monitoring & Evaluation)
- Biostatistics & Epidemiology Units
- Scientific Publishing and Research Editorial Support Roles