#### Topics

##### Linear equations in two variables

- Linear Equation in Two Variables
- Cross - Multiplication Method
- Substitution Method
- Elimination Method
- Graphical Method of Solution of a Pair of Linear Equations
- Equations Reducible to a Pair of Linear Equations in Two Variables
- Simple Situational Problems
- Determinant of Order Two
- Cramer’s Rule for System of Equations in Three Variables
- Pair of Linear Equations in Two Variables

##### Quadratic Equations

- Quadratic Equations
- Roots of a Quadratic Equation
- Solutions of Quadratic Equations by Factorization
- Solutions of Quadratic Equations by Completing the Square
- Formula for Solving a Quadratic Equation
- Nature of Roots of a Quadratic Equation
- The Relation Between Roots of the Quadratic Equation and Coefficients
- To Obtain a Quadratic Equation Having Given Roots
- Application of Quadratic Equation

##### Arithmetic Progression

- Introduction to Sequence
- Geometric Mean
- Arithmetic Progressions Examples and Solutions
- Arithmetic Progression
- Geometric Progression
- General Term of an Arithmetic Progression
- General Term of an Geomatric Progression
- Sum of First n Terms of an AP
- Sum of the First 'N' Terms of an Geometric Progression
- Arithmetic Mean - Raw Data
- Terms in a sequence
- Concept of Ratio

##### Financial Planning

##### Probability

- Basic Ideas of Probability
- Probability - A Theoretical Approach
- Type of Event - Elementry
- Type of Event - Complementry
- Type of Event - Exclusive
- Type of Event - Exhaustive
- Equally Likely Outcomes
- Probability of an Event
- Concept Or Properties of Probability
- Addition Theorem
- Random Experiments
- Sample Space
- Basic Ideas of Probability

##### Statistics

- Tabulation of Data
- Inclusive and Exclusive Type of Tables
- Median of Grouped Data
- Mean of Grouped Data
- Graphical Representation of Data as Histograms
- Frequency Polygon
- Concept of Pie Graph (Or a Circle-graph)
- Concept of Pie Graph (Or a Circle-graph)
- Ogives (Cumulative Frequency Graphs)
- Applications of Ogives in Determination of Median
- Relation Between Measures of Central Tendency
- Introduction to Normal Distribution
- Properties of Normal Distribution
- Graphical Representation of Data as Histograms
- Mode of Grouped Data

#### notes

If a die is thrown, any of the numbers from 1, 2, 3, 4, 5, 6 may appear on the upper face. It means that each number is equally likely to occur. However, if a die is so formed that a particular face come up most often, then that die is biased. In this case the outcomes are not likely to occur equally.

Here, we assume that objects used for random experiments are fair or unbiased. A given number of outcomes are said to be equally likely if none of them occurs in preferance to others. For example if a coin is tossed, possibilities of getting head or tail are equal. A die, having numbers from 1 to 6 on its different faces, is thrown. Check the possibility of getting one of the numbers. Here all the **outcomes are eqully likely**.

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