Search

CBSE Syllabus for Class 12 Board Exam 2020: Applied Mathematics

Check CBSE Syllabus for Class 12 Applied Mathematics board exam 2020. This CBSE Syllabus is important for the preparation of Class 12 Applied Mathematics subject.

Mar 16, 2020 18:35 IST
facebook IconTwitter IconWhatsapp Icon
CBSE
CBSE

Get CBSE Syllabus for Class 12 Applied Mathematics board exam 2020. This CBSE Syllabus is important for the preparation of CBSE Class 12 Applied Mathematics board exam 2020.

ASSESSMENT PATTERN FOR CLASS XII:

Theory

70 marks

Practical

30 marks

Total

100 marks

CLASS XII - SESSION: 2019-2020

UNIT

MARKS

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.

14

2.  Algebra

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

7

3.  Logical Reasoning

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

8

4.  Commercial Mathematics

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

10

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).

10

6.  Two dimensional Geometry

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

4

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.

10

8.  Analysis of time based Data

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

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

7

TOTAL MARKS (THEORY)

70

SUGGESTIVE PROJECTS (FOR 30 MARKS)

  • Algorithmic approach of Sieve of Erastosthene’s.
  • Ramanujan’s theory of prime numbers: Use of prime numbers in coding and decoding of messages.
  • Bertrnad’s postulate
  • Download http://pib.nic.in/prs/2011/latest31mar.pdf.  Analyse various information that have been extracted from the Census, 2011. Understand as to how these information have been presented.
  • Visit   the    census    site    of    India    http://www.censusindia.gov.in/Census_Data_2001/ Census_Data_Online/Language/State ment3.htm. Depict the information given there in a pictorial form.
  • Preparea questionnaire to collect information about money spent by your friends in a month on activities like traveling, movies, recharging of the mobiles, etc. and draw interesting conclusions.
  • Checkout the local newspaper and cut out examples of information depicted by graphs. Draw your own conclusions from the graph and compare it with the analysis given in the report.
  • Analysis of population migration data – positive and negative influence on urbanization.
  • Eachday newspaper tells us about the maximum temperature, minimum temperature, and humidity. Collect the data for a period of 30 days and represent it graphically. Compare it with the data available for the same time period for the previous year.
  • Draw acareer graph of a cricketer (batting average for a batsman and bowling average for a bowler). Conclude the best year of his career. It may be extended for other players also – tennis, badminton, athlete.
  • Share market data analysis – correlation and extreme fluctuation.
  • Vehicle registration data – correlating with pollution and number of accidents.
  • Visita village near Delhi and collect data of various crops over past few years from the farmers. Also collect data about temperature variation and rain over the period for a particular crop. Try to find the effect of temperature and rain variations on various crops.
  • How safe are privately owned public transport versus government owned public transport?

Collect the data from archives about accidents of Blue Line buses and compare with those of DTC buses. Verify whether DTC buses are significantly safer.

  • Visit Kirana shops near your home and collect the data of sale of certain commodities over a month. Try to figure out the stock of a particular commodity which should be in the store in order to maximize the profit.
  • MendelianGenetics: Genes are molecular units of heredity and carry certain information. They occur in pairs. Gregor Mendel studied about the inheritance in pea plants. One of the characteristics about their inheritance is smooth (S) and wrinkled (W). Suppose a plant has a heterogeneous gene that contains both the characteristic S and W. Find the probability of having a heterogeneous offspring (SW) or a homogeneous offspring (SS or WW) in the first generation, second generation, third generation, ….
  • Choose any week of your ongoing session. Collect data for the past 10 – 15 years for the amount of rainfall received in Delhi during that week. Predict amount of rainfall for the current year.
  • Stock price movement using the Binomial Distribution.
  • Weather prediction (prediction of monsoon from past data).
  • Risk assessments by insurance firms from data.
  • Predicting stock market crash.
  • Predicting outcome of election – exit polls.
  • Predicting mortality of infants.
  • Studying various games that use the concept of Probability – Lotto, Throwing dice, Khul Ja Sim Sim, etc.
  • Data from iterative map for population growth – dynamics from plots.
  • Statistical analysis of alphabets/ words appearing in a given text.
  • Statistical methods for drug testing.
  • Modelling population growth through data.
  • Modelling spread of disease through data.
  • Validation of existing models through data.

Related Stories