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The M.Sc. Applied Statistics and Data Analytics programme is an advanced, industry-aligned postgraduate degree designed to build strong analytical, statistical, and computational competencies. As organizations increasingly depend on data-driven ways of decision-making, the demand for professionals skilled in statistical modelling, machine learning, big data analytics, and computational tools continues to soar across sectors such as healthcare, finance, business, public policy, technology, and research.
Applied Statistics provides the foundation for scientific data analysis through probability theory, estimation, hypothesis testing, regression modelling, multivariate techniques, sampling, and statistical quality control. These tools enable students to extract meaningful insights, make predictions, and support evidence-based decisions.
Data Analytics, on the other hand, focuses on transforming raw data into actionable intelligence using computational, algorithmic, and visualization techniques. Students gain hands-on exposure to modern analytical ecosystems including Python, R, SQL, machine learning frameworks, visualization tools, and big data platforms. Together, Applied Statistics and Data Analytics create a powerful combination of theoretical depth and practical proficiency, preparing graduates for data-intensive roles in corporate, government, research institutions, and academia. The curriculum blends rigorous statistical theory with real-world applications, case studies, industry projects, internships, and software-driven learning.
Probability theory, estimation, hypothesis testing, regression modelling, multivariate techniques, sampling, and statistical quality control.
Hands-on exposure to Python, R, SQL, machine learning frameworks, visualization tools, and big data platforms.
Real-world applications, case studies, industry projects, internships, and evidence-based decision-making across high-demand sectors.
An advanced postgraduate degree building analytical, statistical, and computational competencies for high-impact, data-driven careers.
Programme Title: MSc
Specialization: Applied Statistics and Data Analytics
Duration: 2 years
Study Mode: Full time
Core Academic Focus Areas: Statistical Computing & Programming, Data Analytics & Visualization, Statistical Modelling, Machine Learning & Predictive Analytics, Database & Big Data Analytics, Statistical Quality Control, Survey & Research Analytics, Industry-Based Case Studies, Statistical Consultancy & Research Projects, and Capstone/Dissertation.
Learning Pathway: Advanced Data Science, Machine Learning & AI, Advanced Statistical Methods, Business & Financial Analytics, Healthcare & Biostatistics, Data Visualization & Decision Intelligence, Research & Professional Skills, Industry Certifications & Workshops, Experiential Learning, and Dissertation/Capstone Pathway.
Comprehensive semester-wise course distribution covering applied statistical foundations, machine learning, R and SQL practicals, and data analysis labs.
Review the mandatory academic qualifications and minimum score criteria required for admission.
Candidates who have completed a Bachelor’s degree in Statistics / Mathematics / Computer Science / Data Science / Economics / Engineering or any relevant discipline with a minimum of 50% aggregate or equivalent CGPA are eligible.
Basic proficiency in mathematics and an interest in data-driven problem solving are essential.
Looking for a programme that matches your interests?
Find Programmes by InterestTargeted competencies and practical mastery achieved by graduates throughout their academic journey.
PSO1: Demonstrate advanced knowledge of theoretical and applied statistical concepts, probability distributions, inference, and multivariate techniques.
PSO2: Apply machine learning algorithms, computational tools, and predictive analytics to solve complex real-world problems.
PSO3: Demonstrate proficiency in statistical computing, data wrangling, and programming using R, Python, and SQL.
PSO4: Transform and interpret complex data through advanced data visualization, dashboard development, and business storytelling.
PSO5: Design and execute industry-oriented projects, statistical quality control workflows, and evidence-based decision systems across diverse sectors.
PSO6: Formulate systematic scientific research, consultancy solutions, and capstone dissertations adhering to professional and ethical standards.
Key strengths, experiential learning, and strategic career advantages offered by the programme.
Organisations across healthcare, finance, business, public policy, and technology increasingly depend on data-driven decision-making. Professionals skilled in statistical modelling, big data analytics, and machine learning are in high demand globally.
The M.Sc. Applied Statistics and Data Analytics at Kristu Jayanti builds robust competencies through rigorous statistical theory, software-driven learning, real-world case studies, industry projects, and hands-on laboratory practicals.
Choosing this programme enables students to:
With dual strength in applied statistics and data analytics, graduates are prepared for data-intensive roles across corporate, government, research, and academia.