ISI Admission Test 2025: Latest Exam Pattern (Part I & II), Marking Scheme & Number of Questions

The Indian Statistical Institute (ISI) has officially announced that the ISI Admission Test for the 2025 academic session is scheduled to be held on May 11, 2025. The Indian Statistical Institute (ISI), Kolkata, will release the ISI Admission Test 2025 exam pattern on its official website, isical.ac.in.

As per the ISI Admission Test 2025 exam pattern, the test is divided into two parts: Part 1 and Part 2. Part 1 is mandatory for all candidates and consists of multiple-choice and descriptive questions focusing on undergraduate-level Mathematics. Part 2 is subject-specific and varies based on the program applied for. It includes questions from various engineering and science disciplines, requiring candidates to demonstrate their expertise in relevant subject areas. The test is designed to assess candidates' analytical, mathematical, and problem-solving skills, making it a crucial step in the selection process for ISI programs.

ISI Admission Test 2025 Exam Pattern for Part 1

The ISI Admission Test 2025 Part 1 is designed to assess candidates' proficiency in undergraduate-level Mathematics. This section consists of both Multiple Choice Questions (MCQs) and Descriptive questions, evaluating conceptual understanding and problem-solving skills. A total of 30 questions are included, with a maximum score of 120 marks. 

Candidates are given 2 hours to complete the test. The marking scheme awards 4 marks for each correct answer, while no marks are deducted for incorrect responses. However, unlike conventional marking patterns, candidates receive 1 mark for each unattempted question, encouraging strategic question selection.

ISI Admission Test 2025 Exam Pattern for Part 2

The ISI Admission Test 2025 Part 2 consists of both Multiple Choice Questions (MCQs) and Descriptive questions, designed to assess candidates' technical knowledge and problem-solving skills. The test covers five key subjects: Computer Science, Engineering Mechanics, Engineering Drawing, Thermodynamics, and Electrical & Electronics Engineering. 

A total of nine questions are provided, divided into three sections. Candidates are required to attempt four questions - one from each section and an additional question from any section of their choice. The maximum score for this section is 120 marks. Each correct answer is awarded 30 marks, while no marks are deducted for incorrect or unattempted questions. This structure allows candidates to showcase their expertise across multiple engineering disciplines while maintaining flexibility in question selection.

ISI Admission Test 2025 Syllabus

The Indian Statistical Institute (ISI) conducts the ISI Admission Test every year for admission to various undergraduate, postgraduate, and diploma programs in Statistics, Mathematics, Data Science, Economics, Quality Management, Library & Information Science, Computer Science, Cryptology, and Operations Research. The syllabus for the ISI Admission Test varies depending on the program and is designed to evaluate a candidate’s mathematical ability, statistical reasoning, data analysis, programming skills, and subject-specific knowledge. Below is the detailed syllabus for each program, covering all the subjects tested in the ISI Admission Test 2025.

Bachelor of Statistics (B.Stat Hons) and Bachelor of Mathematics (B.Math Hons) Syllabus

The B.Stat and B.Math admission tests assess a candidate’s mathematical ability and problem-solving skills. The exam consists of two papers:

Paper I (UGA – Multiple-Choice Questions): This paper tests fundamental mathematical concepts and reasoning ability.

Paper II (UGB – Descriptive Questions): This paper assesses problem-solving abilities in mathematics through detailed, step-by-step solutions.

Syllabus for B.Stat & B.Math

Algebra

• The test includes topics in set theory, including operations on sets, power sets, and Venn diagrams.
• Candidates are expected to have a strong grasp of the number system, covering natural numbers, integers, rational numbers, irrational numbers, and real numbers.
• Divisibility rules, greatest common divisor (GCD), least common multiple (LCM), and their properties are important topics.
• Modular arithmetic and congruences are tested, along with their applications.
• Polynomials, including factorization, the remainder theorem, and relations between roots and coefficients, are included in the syllabus.
• The topic of complex numbers involves properties such as modulus, conjugates, and representation in the Argand plane.
• Candidates should understand logarithmic functions, their properties, and laws of logarithms.
• The test also covers permutations and combinations, the binomial theorem, and their applications in probability.
• Matrices and determinants are also included, along with operations on matrices, inverse matrices, and solutions of linear equations using matrices.

Geometry

• The syllabus includes Euclidean geometry, covering properties of triangles, quadrilaterals, circles, and basic geometric theorems.
• Coordinate geometry covers the distance formula, section formula, and the equations of lines, circles, parabolas, ellipses, and hyperbolas.
• Mensuration includes perimeter and area of two-dimensional figures, as well as surface area and volume calculations for three-dimensional objects.

Trigonometry

• Candidates must be familiar with trigonometric functions, their properties, graphs, and periodicity.
• The syllabus includes solving trigonometric equations, applications of sine and cosine rules, and problems involving heights and distances.

Calculus

• The test assesses concepts in limits and continuity, including the fundamental properties of limits and the application of L'Hôpital’s Rule.
• Differentiation is covered extensively, including the chain rule, product rule, quotient rule, and applications such as finding tangents, maxima, and minima.
• Integration is tested through definite and indefinite integrals, as well as techniques such as integration by substitution and integration by parts.
• Basic concepts of differential equations, particularly first-order equations and their applications, are included.

Bachelor of Statistical Data Science (BSDS Hons) Syllabus

The BSDS admission test consists of a single test focusing on mathematics and data science. The test evaluates a candidate’s ability to think logically and apply mathematical concepts to data analysis.

Syllabus for BSDS

Mathematics & Statistics

• Algebra, covering sets, functions, sequences, and logarithms.
• Calculus, including limits, differentiation, integration, and differential equations.
• Geometry & Vectors, focusing on coordinate geometry, straight lines, circles, vectors, and planes.
• Trigonometry, including basic trigonometric identities and inverse trigonometric functions.
• Statistics & Probability, covering descriptive statistics, probability rules, Bayes' theorem, random variables, and common distributions such as Binomial, Poisson, and Normal distributions.

Data Science & Logical Reasoning

• The test evaluates logical reasoning through pattern recognition, number series, coding-decoding, and computational thinking.
• Candidates should be familiar with basic data visualization techniques and how to interpret data in different formats.

Master of Statistics (M.Stat) Syllabus

The M.Stat admission test is designed to evaluate advanced skills in Mathematics and Statistics. The exam consists of:

• Paper I (PSA – Multiple-Choice Questions) covering fundamental concepts.
• Paper II (PSB – Descriptive Questions) involving advanced statistical problem-solving.

Syllabus for M.Stat

Mathematics

• Linear Algebra, covering vector spaces, matrices, determinants, eigenvalues, and eigenvectors.
• Real Analysis, including sequences, series, limits, and functions of several variables.
• Coordinate Geometry, covering equations of straight lines, circles, conics, and transformations.
• Differential Equations, including both ordinary and partial differential equations.

Statistics & Probability

• Probability Theory, covering random variables, probability distributions, moment-generating functions, and limit theorems.
• Statistical Inference, covering estimation, hypothesis testing, confidence intervals, and regression analysis.
• Sampling Distributions, including the Central Limit Theorem, Chi-square tests, and analysis of variance (ANOVA).

Master of Mathematics (M.Math) Syllabus

The M.Math admission test assesses advanced mathematical reasoning. The test consists of:

• Paper I (Objective Questions) covering core mathematical concepts.
• Paper II (Descriptive Questions) requiring detailed problem-solving.

Syllabus for M.Math

• Abstract Algebra, covering groups, rings, fields, and homomorphisms.
• Linear Algebra, including vector spaces, eigenvalues, diagonalization, and matrix factorizations.
• Real and Complex Analysis, covering functions of real and complex variables, contour integration, and Cauchy’s theorem.
• Differential Equations, including first and second-order equations, Fourier series, and Laplace transforms.

Master of Science in Quantitative Economics [MS(QE)] Syllabus

The MS(QE) admission test consists of Mathematics, Statistics, and Economics questions.

Syllabus for MS(QE)

Mathematics & Statistics

• Linear Algebra, covering matrix operations and vector spaces.
• Calculus, including differentiation, integration, and optimization.
• Probability, including random variables, expectation, and hypothesis testing.

Economics

• Microeconomics, covering demand-supply, market equilibrium, and game theory.
• Macroeconomics, covering IS-LM models, inflation, and monetary policy.

Master of Science in Quality Management Science [MS (QMS)] Syllabus

The MS (QMS) program focuses on statistical quality control, operations research, and management sciences. The entrance test evaluates a candidate’s knowledge of Probability, Statistics, Operations Research, and Quality Management Techniques.

Syllabus for MS (QMS)

Mathematics & Statistics

• Probability & Random Variables – Basic probability rules, conditional probability, independence, Bayes’ theorem.
• Statistical Distributions – Binomial, Poisson, Normal, Exponential, and other standard distributions.
• Statistical Inference – Estimation, confidence intervals, hypothesis testing, and regression analysis.

Operations Research & Quality Management

• Linear Programming – Formulation, simplex method, duality, and sensitivity analysis.
• Queuing Theory – Poisson processes, birth-death processes, M/M/1 and M/M/k models.
• Quality Control Techniques – Control charts for variables and attributes, process capability analysis.

Master of Science in Library and Information Science [MS (LIS)] Syllabus

The MS (LIS) program focuses on library classification, information retrieval, knowledge management, and digital archiving. The entrance exam assesses a candidate’s understanding of library sciences, digital information systems, and bibliometric analysis.

Syllabus for MS (LIS)

• Library & Information Science Fundamentals – Classification, cataloging, indexing.
• Digital Libraries & Knowledge Management – Metadata standards (Dublin Core, MARC), digital preservation.
• Information Retrieval & Bibliometrics – Search engines, Boolean logic, citation analysis.

Master of Technology in Computer Science [M.Tech (CS)] Syllabus

The M.Tech (CS) program focuses on computer science, data structures, algorithms, and machine learning. The entrance test consists of:

• Paper I (Multiple-Choice Questions) – Covers Mathematics & Computer Science.
• Paper II (Descriptive Questions) – Covers Algorithms & Programming.

Syllabus for M.Tech (CS)

Mathematics

• Discrete Mathematics – Sets, relations, functions, logic, combinatorics, graph theory.
• Linear Algebra – Matrices, determinants, eigenvalues, eigenvectors.
• Probability & Statistics – Random variables, distributions, Bayes' theorem.

Computer Science

• Data Structures & Algorithms – Trees, graphs, sorting, searching, dynamic programming.
• Programming – C, C++, Java, Python, object-oriented programming.
• Operating Systems – Process scheduling, memory management, file systems.
• Databases – SQL, NoSQL, normalization, transactions.
• Computer Networks – OSI model, TCP/IP, routing algorithms.

Master of Technology in Cryptology and Security [M.Tech (CrS)] Syllabus

The M.Tech (CrS) program is focused on cryptographic algorithms, information security, and cybersecurity. The entrance test evaluates mathematics, cryptography, and security concepts.

Syllabus for M.Tech (CrS)

Mathematics & Number Theory

• Modular Arithmetic – Fermat’s theorem, Euler’s theorem.
• Number Theory – Prime numbers, GCD, LCM, Chinese Remainder Theorem.

Cryptography & Security

• Symmetric & Asymmetric Encryption – AES, DES, RSA, Diffie-Hellman.
• Hashing Functions – MD5, SHA, HMAC.
• Cybersecurity – Network security, authentication protocols, intrusion detection.

Master of Technology in Quality, Reliability & Operations Research [M.Tech (QROR)] Syllabus

The M.Tech (QROR) program emphasizes quality management, reliability analysis, and optimization techniques. The entrance exam consists of probability, statistics, and operations research concepts.

Syllabus for M.Tech (QROR)

Probability & Statistics

• Random Variables & Probability Distributions – Normal, Poisson, Exponential distributions.
• Statistical Inference – Estimation, hypothesis testing, confidence intervals.

Operations Research & Quality Control

• Linear Programming – Formulation, simplex method, sensitivity analysis.
• Reliability Engineering – Failure rates, hazard functions, Weibull distributions.
• Six Sigma & Quality Control – Process capability, control charts.

Postgraduate Diploma in Statistical Methods & Analytics Syllabus

The PG Diploma in Statistical Methods & Analytics provides training in statistics, data analysis, and predictive modelling. The entrance test covers basic mathematics, statistics, and data visualization.

Syllabus for PG Diploma in Statistical Methods & Analytics

Mathematics & Statistics

• Basic Algebra & Calculus – Functions, limits, differentiation, integration.
• Probability & Distributions – Random variables, expectation, variance.
• Statistical Inference – Confidence intervals, hypothesis testing.

Data Analytics & Machine Learning

• Data Visualization – Bar charts, histograms, scatter plots.
• Regression Analysis – Linear & multiple regression models.
• Introduction to Machine Learning – Supervised & unsupervised learning.

Postgraduate Diploma in Computer Applications Syllabus

The PG Diploma in Computer Applications focuses on programming, software development, and database management. The entrance test evaluates logical reasoning, programming, and computer fundamentals.

Syllabus for PG Diploma in Computer Applications

Programming & Data Structures

• C, C++, Java, Python – Basic syntax, loops, functions, object-oriented programming.
• Data Structures – Arrays, linked lists, stacks, queues, trees, graphs.

Database Management & Software Engineering

• SQL & NoSQL Databases – Normalization, transactions, indexing.
• Software Engineering Principles – SDLC, Agile methodologies.

Operating Systems & Networks

• Operating Systems – Process management, memory management, file systems.
• Computer Networks – Networking protocols, TCP/IP model, OSI layers.

ISI Admission Test Exam Pattern 2025 FAQs