# KVPY Exam Preparation

**KVPY** (**K**ishore **V**aigyanik **P**rotsahan **Y**ojana) is an exam-based fellowship in India. This page outlines the exam details and math topics covered, providing relevant wikis and quizzes for training and practice. Other sciences are covered on the exam, but are not currently covered on this page.

## Exam Information

The first round of the selection procedure is an aptitude test. Generally, the cut off is seen to be around 45%-60% of the total marks but it may vary according to the toughness of the paper. Then, based on the performance in the aptitude test, short-listed students are called for an interview which is the final stage of the selection procedure. For receiving a fellowship, both aptitude test and interview marks are considered.

## Basic Topics

These are the basic topics covered by KVPY. This is a great place to start learning if you’re new to KVPY!

$\large \textbf{Algebra}$

$\large \textbf{Geometry}$

$\large \textbf{Combinatorics (Counting and Probability)}$

ChapterWikiQuizSet Operations Principle of Inclusion/Exclusion Understanding Data

$\large \textbf{Calculus}$

## Intermediate Topics

These are the intermediate topics covered by KVPY. This is a great place to hone your skills if you are already comfortable with solving the first few problems on KVPY.

$\large \textbf{Algebra}$

$\large \textbf{Geometry}$

$\large \textbf{Combinatorics (Counting and Probability)}$

ChapterWikiQuizRules of Sum and Product Combinations Discrete Probability Expected Value

$\large \textbf{Calculus}$

ChapterWikiQuizHigher Order Derivatives L'Hopital's Rule Related Rates Extrema

## Advanced Topics

These are the advanced topics covered by KVPY, which usually appear in the later problems. This is a great place to learn to solve the hardest problems on the KVPY if you're shooting for a perfect score!

$\large \textbf{Algebra}$

$\large \textbf{Geometry}$

$\large \textbf{Combinatorics (Counting and Probability)}$

ChapterWikiQuizConditional Probability Geometric Probability Binomial Distribution

$\large \textbf{Calculus}$

**Cite as:**KVPY Exam Preparation.

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