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Preparing for the RBI Grade B DSIM exam can feel confusing at the start. The syllabus looks long and technical, and many aspirants are not sure where to begin. But once you understand the paper structure and subject-wise topics, your preparation becomes more clear and focused. In this blog, we have provided the RBI Grade B DSIM syllabus, paper pattern, and detailed statistics topics.
RBI Grade B DSIM Syllabus 2026
RBI Grade B DSIM syllabus is designed to test candidates' knowledge of statistics, data analysis, econometrics, and data science used in policy research at the Reserve Bank of India. It is based on a postgraduate level and includes both theory and practical applications. The syllabus covers important topics such as probability, regression, statistical inference, time series analysis, machine learning, optimization techniques, and database management systems.
The exam has 3 papers. Paper 1 is objective Statistics, Paper 2 is descriptive Statistics, and Paper 3 is English writing skills. Paper 1 and Paper 2 focus on advanced statistical and analytical concepts, while Paper 3 tests writing ability, clarity, and understanding of economic and financial topics.
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What is the RBI Grade B DSIM exam pattern?
The RBI Grade B DSIM exam mainly tests the knowledge of statistics, econometrics, data science, and English writing skills. The selection process includes three written papers and an interview stage. Paper 1 is objective, while Papers II and III are descriptive in nature.
| Paper | Type | Subject | Duration | Marks |
|---|
| Paper 1 | Objective | Statistics | 120 Minutes | 100 |
| Paper 2 | Descriptive | Statistics | 180 Minutes | 100 |
| Paper 3 | Descriptive | English Writing | 90 Minutes | 100 |
| Interview | Personality + Technical | — | — | 75 |
When are the RBI Grade B phase 1 and phase 2 exams scheduled?
RBI Grade B Exam 2026 schedule along with the official notification. Phase 1 (Prelims) is expected to be held in June 2026, while Phase 2 (Mains) is scheduled for July 2026. The exact exam dates may vary for the General, DEPR, and DSIM streams. Candidates should carefully note these dates and start their preparation early, as proper planning is important to perform well in both stages.
| Event | General Post | DEPR Post | DSIM Post |
|---|
| Phase 1 Exam Date | 13 June 2026 | 14 June 2026 | 14 June 2026 |
| Phase 2 Exam Date | 25 July 2026 | 26 July 2026 | 26 July 2026 |
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What topics are covered in the RBI Grade B DSIM paper-wise syllabus?
The RBI Grade B DSIM paper-wise syllabus focuses mainly on advanced statistics, econometrics, data science, and analytical skills required for data modeling and policy research at the Reserve Bank of India. The exam includes three papers, where Paper 1 and Paper 2 cover detailed statistics topics at a post-graduation level, while Paper 3 evaluates English writing ability and expression skills. Below are the main topics covered in each paper as per the official syllabus.
| Paper | Type | Topics (Simple Pointers) |
|---|
| Paper 1 | Objective (Statistics) | • Probability theory and distributions
• Sampling theory and methods
• Linear models and economic statistics
• Statistical inference and non-parametric tests
• Stochastic processes
• Multivariate analysis
• Econometrics and time series models
• Optimization and statistical computing
• Data science, AI and machine learning
• Database and data warehouse management |
| Paper 2 | Descriptive (Statistics) | • Estimation methods and hypothesis testing
• Regression models (Ridge, LASSO, Elastic Net)
• Index numbers and inequality measures
• Markov chains, Poisson process, Brownian motion
• ARIMA, SARIMA, ARCH/GARCH models
• Bayesian modelling, simulation, MCMC methods
• Neural networks, classification and clustering
• SQL queries, RDBMS, ETL and data warehousing |
| Paper 3 | Descriptive (English) | • Essay writing for analytical thinking
• Precis writing and comprehension
• Clear expression and structured writing
• Understanding and explaining topics in writing |
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What are the topics covered under the RBI DSIM paper 1 syllabus?
Paper 1 of the RBI Grade B DSIM exam is an objective-type statistics paper that checks your conceptual clarity, analytical ability, and technical knowledge. The syllabus is based on post-graduation-level statistics and includes probability, econometrics, machine learning, optimization, and database concepts that are useful for data analysis and policy research at RBI.
| Main Topic | Sub Topics Covered |
|---|
| Theory of Probability, Distributions & Sampling | • Classical and axiomatic probability • Bayes theorem • Laws of Large Numbers (LLN) and Central Limit Theorem (CLT) • Characteristic functions and probability inequalities • Binomial, Poisson, Normal, Beta, Gamma, Weibull, Logistic distributions • Chi-square, t, F, Z distributions • Sampling methods – SRS, stratified, cluster, PPS • Ratio and regression estimation |
| Linear Models & Economic Statistics | • Linear algebra, matrices, quadratic forms • Simple and multiple regression • Gauss-Markov setup and weighted least squares • Dummy variables and multicollinearity • Ridge, LASSO, Elastic Net • Index numbers, Gini coefficient, Lorenz curve • National accounts basics |
| Statistical Inference | • Estimation concepts and MVUE • Rao-Blackwell, Lehmann-Scheffe, Cramer-Rao bound • MLE, least squares, minimum Chi-square • Bayes estimators • Hypothesis testing and Neyman-Pearson theory • Likelihood ratio tests • Non-parametric tests • Kernel density estimation |
| Stochastic Processes | • Poisson and compound Poisson process • Markov chains and Chapman-Kolmogorov equations • Stationary distributions • Brownian motion and martingales |
| Multivariate Analysis | • Multivariate normal distribution • Logit and probit models • Principal Component Analysis (PCA) • Factor analysis • Canonical correlation • Discriminant analysis • Cluster analysis |
| Econometrics & Time Series | • OLS and GLS methods • Heteroscedasticity and autocorrelation tests • Instrumental variables and panel regression • AR, MA, ARMA models • ARIMA and SARIMA • Box-Jenkins methodology • ARCH/GARCH models |
| Optimization & Statistical Computing | • Taylor theorem and convex functions • Newton and gradient methods • Lagrange multipliers • Linear programming and simplex method • Simulation and bootstrap methods • EM algorithm • Bayesian estimation and MCMC |
| Data Science, AI & Machine Learning | • Linear and logistic regression • Naïve Bayes and SVM • Decision trees and neural networks • Random forest and boosting • Clustering techniques • NLP basics • Feature selection and cross-validation |
| Database & Data Warehouse Management | • RDBMS fundamentals • SQL queries and joins • Database normalization • NoSQL databases • ETL processes • OLAP vs OLTP • Indexing and big data basics |
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What are the topics covered under the RBI Grade B DSIM paper 2 syllabus?
Paper 2 is a descriptive statistics paper and follows the same syllabus areas as Paper 1, but the focus is on detailed explanations, derivations, and applied analytical writing. Candidates are expected to demonstrate deeper understanding of statistical theory, econometric modeling, and data science applications through structured answers.
| Main Topic | Sub Topics Covered |
|---|
| Probability & Sampling (Descriptive Level) | • Laws of probability • Distribution properties • Asymptotic distributions • Contingency tables • Sampling designs • Survey errors and non-response issues |
| Linear Models & Regression Analysis | • Polynomial regression • Box-Cox transformation • Regression with correlated observations • Hypothesis testing in regression • Confidence regions • Outlier detection and treatment |
| Economic Statistics | • Construction of index numbers • Base shifting and splicing • Deflating of index numbers • Measurement of inequality • Basics of macroeconomic statistics |
| Statistical Inference | • Likelihood ratio tests • Bartlett's test • Kolmogorov–Smirnov test • Wilcoxon tests and Friedman test • Order statistics |
| Stochastic Processes | • Non-homogeneous Poisson process • Recurrent events • Stationary distributions • Random walk limits |
| Multivariate & Classification Methods | • PCA interpretation • Factor loadings • Discriminant rules • Cluster validation indices |
| Econometrics & Time Series | • Simultaneous equation models • Distributed lag models • ARIMA diagnostics • Stationarity tests • Volatility modelling |
| Optimization & Computing | • Gradient-based optimization • Bayesian modelling • Gibbs sampling • Metropolis-Hastings algorithm • Robust regression techniques |
| Machine Learning Applications | • Random forest • Boosting techniques • Neural networks • Kernel regression • Feature engineering and hyperparameter tuning |
| Database Systems | • SQL operations • Data integration • Data warehouse schemas • Indexing and query optimization |
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What are the topics covered under the RBI DSIM paper 3 syllabus?
Paper 3 is a descriptive English paper designed to assess communication skills, clarity of thought, and professional writing ability. RBI expects DSIM candidates to interpret data insights and present them clearly, so this paper focuses on structured writing rather than technical statistics.
| Section | Skills and Topics Covered |
|---|
| Essay Writing | Analytical writing on economic, financial, or social themes |
| Precis Writing | Summarizing information clearly and logically |
| Reading Comprehension | Understanding and interpreting passages |
| Expression & Writing Skills | Grammar usage, clarity, coherence, professional tone |
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