Admission Notice for MSc in Statistics (2025 Intake)
Last Date for Online Application: 12.05.2025, 11 AM
St. Xavier’s University, Kolkata
The MSc in Statistics programme at St. Xavier’s University, Kolkata, is designed to provide students with a strong foundation in statistical theory and practical applications. Launched in 2022, the programme emphasizes analytical and quantitative skills, preparing students for careers in analytics, data science, and research. The curriculum is industry-relevant, combining theoretical knowledge with hands-on training using state-of-the-art computing facilities and modern statistical tools.
MSc in Statistics Program
- Specializations: Industrial Statistics, Business Analytics, or Biostatistics.
- Duration: 2 Years (4 Semesters).
- Class Timings: Regular classes from 10:00 AM to 3:40 PM, with remedial classes and activities from 3:45 PM to 5:00 PM.
- Placement & Internship Opportunities: Assistance provided for internships and placements in top organizations.
- Merit Scholarships: Up to 100% tuition fee waiver based on undergraduate marks.
- Infrastructure: Advanced lab facilities with the latest statistical software and tools.
- Faculty: Experienced full-time faculty supported by visiting experts from reputed institutions and industries.
Admission Details:
Eligibility
- Compulsory Courses in UG:
- B.Sc. (Hons.)/Major in Statistics OR
- B.Sc. (Hons.)/Major in Mathematics with Statistics as a general elective subject.
- Aggregate Marks Required:
- 45% for General Category.
- 40% for Reserved Categories (SC/ST/OBC/OBC-A/OBC-B/Divyang (PWD)/Christian).
Selection Process for MSc in Statistics
- Admission is based on the Admission Test Marks.
- Admission Test Details:
- Duration: 2 Hours.
- Format: 100 Multiple Choice Questions (MCQs) – No Negative Marking.
- Syllabus:
- Statistics (70 Marks).
- Mathematics (30 Marks).
See Full Syllabus Below.*
Fee Structure:
- Admission Fee: ₹30,000 (One-Time).
- Security Deposit (Refundable): ₹5,000 (One-Time).
- Alumni Life Membership Fee: ₹5,015 (To be paid along with 4th semester fees).
- Semester Fees:
| Fee Component | Amount (₹) |
|---|---|
| Tuition Fee | 54,000 |
| Development Fee | 7,500 |
| Exam Fee | 2,500 |
| Library Fee | 1,500 |
| IT Infrastructure Fee | 1,000 |
| Sports & Students’ Activity Fee | 1,000 |
| Total Fees (Per Semester) | 67,500 |
How to Apply:
- Visit the official website: www.sxuk.edu.in.
- Register by verifying your mobile number and email ID.
- Complete the online application form and upload the required documents.
- Pay the application fee of ₹500 and submit your application.
- Attend the admission test on the scheduled date.
- Upon selection, complete the document verification and fee payment process.
Contact Information:
- Address: Action Area IIIB, New Town, Kolkata – 700160.
- Website: www.sxuk.edu.in.
- Phone: 033 6624 9881 / 033 6624 9827.
- Email: [email protected].
Syllabus for the PG Admission Test 2025 for MSc in Statistics Program at St. Xavier’s University, Kolkata
Statistics (70 marks)
Probability:
- Set theory
- Permutation and combination
- Theory of probability and its approaches
- Calculation of event probabilities
- Addition and multiplication laws of probability
- Conditional probability
- Theorem of total probability and Bayes’ theorem
- Independence of events
Random Variables:
- Probability mass function (PMF) and density function (PDF)
- Cumulative distribution function (CDF)
- Mathematical expectation, variance, moments, and moment generating function
- Skewness and kurtosis
Standard Distributions:
- Uniform distribution
- Binomial distribution
- Poisson distribution
- Normal distribution
- Exponential distribution
Joint Distributions:
- Joint, marginal, and conditional distributions
- Distribution of functions of random variables
- Simple, multiple, and partial correlation (linear and non-linear)
- Product moment correlation coefficient and its properties
- Simple linear regression, principle of least squares, regression equations, and estimation
- Properties of regression coefficients
- Relationship between correlation and regression coefficients
- Independence of random variables
Sampling Theory:
- Populations and samples
- Parameters and statistics
- Descriptive and inferential statistics
- Sampling techniques: random and non-random sampling
- Types of sampling:
- Simple random sampling
- Stratified sampling
- Cluster sampling
- Two-phase sampling
- Two-stage sampling
- Systematic sampling
- Purposive sampling
- Convenient sampling
- Quota sampling
- Snowball sampling
- Unbiased estimates of population mean and sampling variance
- Sampling distributions of sample mean and sample variance
- Central limit theorem
Estimation:
- Concept of point estimation
- Properties of a good estimator (unbiasedness, consistency, efficiency, and sufficiency)
- Minimum variance unbiased estimator (MVUE)
- Methods of estimation:
- Method of moments
- Method of maximum likelihood
- Least squares method
- Concept of interval estimation
- Confidence intervals for population mean and proportions
Testing of Hypothesis:
- Basic concepts of hypothesis testing
- Small sample and large sample parametric tests using:
- Z-test
- t-test
- Chi-square test
- F-test (for population means and proportions)
Mathematics (30 marks)
Differential Calculus:
- Concepts of limit and continuity of a function
- Rules of differentiation and their applications
- Rate measure, slope, increasing and decreasing functions
- Partial derivatives (up to second order)
- Homogeneity of functions and Euler’s theorem
- Total differentials
- Differentiation of implicit functions using total differentials
- Maxima and minima (including second or higher order derivatives)
Integral Calculus:
- Standard integral forms
- Fundamental theorems of integral calculus
- Methods of integration:
- By substitution
- By parts
- By use of partial fractions
- Definite integration
- Finding areas in simple cases
Matrices:
- Algebra of matrices
- Inverse of a matrix
- Matrix operations and business applications
- Rank of a matrix
- System of linear equations:
- Matrix inversion method
- Cramer’s rule
- Linear transformations
- Eigenvalues and eigenvectors
- Cayley-Hamilton theorem
