Syllabus of Higher Secondary
Standard - 11 & 12
(General Stream - English Medium)
Implemented From June - 2004 in Standard - 11,
Implemented From June - 2005 in Standard - 12

Statistics (135)

Standard: 11

1 Collection of Data

• Population and Sample

• Advantages of Sample Survey

• Quantitative and qualitative data

• Primary and secondary data.

• Difference between primary and secondary data

• Methods of collection of primary data :

  • Direct Inquiry - Merits and demerits

  • Indirect Inquiry - Merits and demerits

  • Questionnaire Method - Merits and demerits

  • Questionnaire by Post - Merits and demerits

  • Questionnaire by enumerators - Merits and demerits

  • Characteristics of ideal questionnaire

  • Construction of questionnaire (new point)

  • Sources of secondary data

  • Uses of secondary data and precautions required to be taken before using secondary data.
    (Examples on construction of questionnaire to be added in the exercise)

2. Classification and Tabulation:

• Variables and Attributes

  • Discrete and continuous variables.

• Data - Quantitative and qualitative.

• Classification - ungrouped and grouped data

• Type of classification

1. Classification of qualitative data
   (i) Simple classification
   (ii) Complex classification

2. Classification of quantitative data

   • Discrete frequency distribution (Examples)

   • Continuous frequency distribution.

   • Cumulative frequency distribution from continuous frequency distributions.

   • Formation of original frequency distribution from cumulative frequency distribution (New Point)

   • Points to be consider for construction of continuous frequency distribution.

   • Tabulation / Types / uses (More illustrations to be given)

   • Guiding principles for preparing tabulations. (More examples to be given for tabulation).

3. Presentation of data by graphs and diagram.

• Importance of Graphs and Diagrams in statistics

• Type of Diagrams

• Questions for interpretation of graphs and diagrams

Note: Practical illustrations of graphs and diagram related to Economics, Budget and commerce, Interpretation of such diagram.

4. Measures of Central Tendency

• Meaning Characteristics of ideal average

• Different measures of central tendency

• Calculation of Mean - Explanation of different types of mean simple arithmetic Mean, Geometric Mean. Weighted Mean, Combined mean (New point)

• Median, Mode, Quartiles, deciles, Percentiles, percentile rank - Calculation of each measure.

5. Dispersion

• Meaning - uses (Note : Meaning of dispersion with the help of limitations of average)

• Measures of dispersion (Note : Explain the concept of absolute and relative measures of dispersion)

• Merits, demerits and utility of measures of dispersion 

• Comparison between measures of central tendency and dispersion with illustrations.

6. Skewness :

• Meaning Types (Note : Examples relating to absolute and relative measure of skewness to be given)

• Measures of skewness

• Methods of calculation of skewness

• Formulae for absolute and relative measure, merits and demerits of each method.

7. Permutation combination and Binomial expansion

• Meaning of permutation

• Meaning of combination

• Meaning of binomial. expansion

• Exercise sums

8. Arithmetic progression

• Introduction

• Arithmetic Progression

• The nth term and sum of the first 'n' terms of AR

• Arithmetic mean

• Assumption related to A. P.

• Arithmetic means

(Note : In addition to the details given in business maths of std. XI, examples related to sigma formula are included)

1. The consistency of usage of statistical formulae from std. 8 to 12th should be maintained.

2. Practical examples illustrations are to be cited in each chapter for easy understanding of students.

3. Consistency of topics is to be maintained in each chapter.

Standard - 12

1. Methods of sampling

• Census and Sample - Meaning & definition importance of sampling.

• Characteristics of good sample, size of sample.

• Methods of sampling - Simple random, Lottery method, random number table stratified sampling.

• Merits and demerits of simple random sample method.

• Mean and variance of sample with replacement and without replacement

• Merits and demerits of stratified random sampling.

• Mean and variance with and without replacement of statified sampling.

2. Index Number :

• Meaning & Definition of Index Number

• Characteristics of Index Number

• Uses of Index Number

• Base Year
  - Fixed Base Method - Merits & Demerits
  - Chain Base Method - Merits & Demerits
  - Exercise examples.

• Conversion of fixed base index numbers into chain base index numbers and of chain base index numbers into fixed base index numbers.

• Calculation of Index Numbers
  - Laspayer - Formula and examples.
  - Paasche - Formula and examples.
  - Fisher - Formula and examples.

• Cost of living index number - Explanation and construction - examples.

• Uses and limitations of cost of living index numbers.
  (Note : Examples of missing information are not in syllabus)

3. Linear Correlation

• Meaning & Definition of linear correlation.

• Coefficient of correlation - definition and methods - scatter diagram method - examples and explanation with illustrations.

• Perfect positive correlation

• Perfect negative correlation

• Partial Positive correlation

• Partial Negative correlation

• Karl Pearson's Product Moment method - examples and illustration.

• Alternative formulae of Karl Pearson

• Spearans Rank correlation method - explanation - merits, demerits & Sums.

• Interpretation of coefficient of correlation and its precautions.

4. Linear Regression

• Introduction

• Linear Regression Model
  

• Fitting a regression line
  (1) Scatter Diagram Method
  (2) Least Square Method

• Regression coefficient

• Different formulae for calculation of regression coefficients.

• Coefficient of determination

• Precautions for using regression coefficient.

• Two regression lines.

• Illustrations

5. Interpolation and Extrapolation

• Meaning and definition

• Uses and importance

• Assumptions

• Method of interpolation and extrapolation
  1. Newton's Method 2. Lagranges Method
  3. Binomial Expansion method.
  (Pascal's triangle explanation - sum of all 3 methods.)
  Note : Proof of any formula is not in syllabus.

6.Series

• Meaning

• Types - base on time - Time series, Other series - Arithmetic progression Geometric Progression.

• Time Series - Meaning - definition - Illustration - sums

• Trend and methods of measuring trends - Graphical method, Least square method.

• Other series - Arithmetic Progression is explained in std. XI

• Geometric progression - Explanation meaning - definition illustrations – sum of the series & sum.

7. Probability

• Introduction

• Random experiment and sample space

• Event - Certain event, impossible event other events.

• Definition of probability
  - Classical definition and assumption.
  - Statistical definition

• Rules of probability

• Sums related to events.
  Note : No proof of rules of probability is included in syllabus.

8. Probability Distribution :

• Random variable - Discrete random variable

• Continuous random variable

• Probability Distribution

• Binomial Probability Distribution.

• Characteristics. of binomial probability distribution.

• Binomial probability function and sums based on it

• Normal distribution.

• Function of Normal distribution.

• Standard Normal variable.

• Standard Normal distribution.

• Area of Normal Curve

• Characteristics of Normal Distribution.

• Characteristics of Standard normal distribution.

• Exercise based on normal and standard normal distributions.

Suggestions :

1. No proof is included in any formulae.

2. Consistency of statistical formulae to be maintained from std. 8 to std. 12.

3. Logical sequence of chapter should be observed.

TOP