Syllabus of Applied Mathematics has been designed with an intention to orient the students towards the mathematical tools relevant in life. Special efforts has been made in order to connect it’s application in various fields, so that, students who are opting for Social Science based subjects or Commerce based subjects or skill based subjects at senior secondary level can also fulfill their urge of learning mathematics joyfully.

1. Fundamentals of Calculus

Basics of Limits & continuity, differentiation of non-trigonometric functions, Basic applications of derivatives in finding Marginal cost, Marginal Revenues etc. Increasing and Decreasing Functions, Maxima / Minima. 

Integration as reverse process of differentiation, integration of simple algebraic functions.

2. Algebra

Introduction of Matrices, Algebra of Matrices, Determinants of Square matrices (Application only).

3. Logical Reasoning

Number series, Coding, decoding and odd man out, direction tests, blood relations, syllogism, Binary numbers, logical operations and truth table.

4. Commercial Mathematics

Calculating EMI, calculations of Returns, Compound annual growth rate (CAGR), Stocks, Shares, Debenture, valuation of Bonds, GST, Concept of Banking.

5. Probability

Introduction to probability of an event, Mutually exclusive events, conditional probability, Law of Total probability.

Basic application of Probability Distribution (Binomial Distribution, Poisson Distribution and Normal Distribution).

6. Two dimensional Geometry

Slope of a line, equation of a line in point slope form, slope intercept form and two point form.

7. Linear Programming

Introduction, related terminology such as constraints, objective function, optimization, different types of LP, mathematical formulation of LP problem, graphical method of solution for problems in two variables.

8. Analysis of time based Data

Index numbers: meaning and uses of index number, construction of index numbers, construction of consumer price indices.

Time series & trend analysis: Component of time series, additive models, Finding trend by moving average method.