CSIR NET Maths topic-wise weightage
Every page that answers this question gives you a range. This one gives you a count — of 594 Part B and Part C questions from 6 complete previous-year papers, each mapped to its syllabus topic. The papers, and how much of each one we hold, are listed first so you can judge the number before you read it.
The papers this is counted from
| Paper | Shifts | Subject Qs held | Coverage | Counted? |
|---|---|---|---|---|
| December 2025 | 1 | 99 of 100 | 99% | yes |
| June 2025 | 1 | 100 of 100 | 100% | yes |
| December 2024 | 2 | 200 of 200 | 100% | yes |
| June 2024 | 1 | 100 of 100 | 100% | yes |
| December 2023 | 1 | 96 of 100 | 96% | yes |
| June 2023 | 1 | 38 of 100 | 38% | excluded — too partial to count |
A paper is counted only when we hold at least 95% of its 100 subject questions per shift. Counting a paper we hold a third of would pull every topic it happens to touch upward and every topic it misses down, invisibly. Of the 595 questions in the counted papers, 594 are mapped to a syllabus topic; the remaining 1 are not yet mapped and are excluded from the percentages below.
The paper, drawn to scale
Four bands, one per unit, each as tall as that unit’s share. Every topic inside is as wide as its share of the unit — so a rectangle’s area is its share of the paper, and the whole picture is one paper.
Weightage by topic
The Part C column matters more than the total: Part C carries 95 of the 200 marks and is scored all-or-nothing.
| Topic | Unit | Questions | of which Part C | Share |
|---|---|---|---|---|
| Probability | Probability, Statistics & Linear Programming | 44 | 27 | 7.4% |
| Eigenvalues and Canonical Forms | Analysis & Linear Algebra | 34 | 23 | 5.7% |
| The Real Line | Analysis & Linear Algebra | 34 | 13 | 5.7% |
| Linear Models and Multivariate | Probability, Statistics & Linear Programming | 32 | 20 | 5.4% |
| Estimation | Probability, Statistics & Linear Programming | 30 | 18 | 5.1% |
| Ordinary Differential Equations | ODE, PDE & Applied Mathematics | 30 | 17 | 5.1% |
| Rings and Fields | Complex Analysis, Algebra & Topology | 29 | 22 | 4.9% |
| Limit Theorems and Markov Chains | Probability, Statistics & Linear Programming | 28 | 16 | 4.7% |
| Vector Spaces and Linear Maps | Analysis & Linear Algebra | 25 | 12 | 4.2% |
| Partial Differential Equations | ODE, PDE & Applied Mathematics | 25 | 12 | 4.2% |
| Groups | Complex Analysis, Algebra & Topology | 24 | 12 | 4% |
| Hypothesis Testing | Probability, Statistics & Linear Programming | 23 | 15 | 3.9% |
| Inner Product Spaces and Forms | Analysis & Linear Algebra | 21 | 10 | 3.5% |
| Continuity and Differentiation | Analysis & Linear Algebra | 20 | 11 | 3.4% |
| Numerical Analysis | ODE, PDE & Applied Mathematics | 18 | 12 | 3% |
| Calculus of Variations | ODE, PDE & Applied Mathematics | 18 | 12 | 3% |
| Linear Integral Equations | ODE, PDE & Applied Mathematics | 16 | 12 | 2.7% |
| Cauchy Theory | Complex Analysis, Algebra & Topology | 15 | 9 | 2.5% |
| Sampling and Design of Experiments | Probability, Statistics & Linear Programming | 14 | 8 | 2.4% |
| Sequences and Series of Functions | Analysis & Linear Algebra | 14 | 9 | 2.4% |
| Analytic Functions | Complex Analysis, Algebra & Topology | 13 | 6 | 2.2% |
| Singularities and Residues | Complex Analysis, Algebra & Topology | 12 | 6 | 2% |
| Functions of Several Variables | Analysis & Linear Algebra | 12 | 12 | 2% |
| Integration | Analysis & Linear Algebra | 12 | 11 | 2% |
| Classical Mechanics | ODE, PDE & Applied Mathematics | 11 | 6 | 1.9% |
| Topology | Complex Analysis, Algebra & Topology | 11 | 8 | 1.9% |
| Zeros and Mappings | Complex Analysis, Algebra & Topology | 9 | 4 | 1.5% |
| Metric Spaces | Analysis & Linear Algebra | 6 | 5 | 1% |
| Lebesgue Measure and Integration | Analysis & Linear Algebra | 6 | 5 | 1% |
| Linear Programming | Probability, Statistics & Linear Programming | 5 | 3 | 0.8% |
| Determinants and Matrix Tricks | Analysis & Linear Algebra | 3 | 2 | 0.5% |
What this does not tell you
- It is not a forecast. These are counts from papers already sat. The mix moves between sessions, and a topic that carried six questions last December is not owed six in June.
- Weightage is not marks. Part C awards nothing for a partly correct selection, so a heavy topic you half-know can return less than a light one you know completely. Frequency tells you where questions have been, not where your marks are.
- The mapping is ours, not CSIR’s. Each question was assigned to a syllabus topic by hand. A question sitting across two topics was filed under one, and reasonable people would file some of them differently.
- 6 papers is a small sample. Enough to see the shape, not enough to separate a 5% topic from a 4% one. Read the ordering, not the decimal.
Citing this
Quoting these figures somewhere? Every one is linked to the document it came from, so the number can be checked rather than taken on trust.
NETMaths, "CSIR NET Mathematical Sciences topic-wise weightage, counted from previous-year papers", 12 September 2026. https://netmaths.in/pyq/weightage
Common questions
- Which topic has the highest weightage in CSIR NET Mathematical Sciences?
- Counted across the 6 complete papers on this site, the heaviest topics are Probability, Eigenvalues and Canonical Forms, The Real Line, Linear Models and Multivariate, Estimation and Ordinary Differential Equations — each carrying roughly 5 to 7 per cent of the subject questions. No single topic dominates, which is why a plan built around three or four favourites tends to fail.
- How is this topic-wise weightage calculated?
- By counting every Part B and Part C question from the previous-year papers transcribed on this site — 594 of them — mapping each to its syllabus topic, and dividing. Only papers held at 95 per cent or more of their subject questions are counted, and the coverage of each is shown on the page above the results.
- Does high weightage mean I should study that topic first?
- Not on its own. Weightage tells you how often a topic has appeared, not how many marks you can reliably earn from it. Part C is scored all-or-nothing, so a heavy topic you half-know can be worth less than a lighter one you know completely.
- Is the weightage the same every year?
- No. These are counts from past papers, not a forecast, and the mix moves between sessions. Treat them as where the questions have been, not where the next ones must be.