Topics
Number Systems
Number Systems
Polynomials
Algebra
Coordinate Geometry
Linear Equations in Two Variables
Geometry
Coordinate Geometry
Introduction to Euclid’S Geometry
Mensuration
Statistics and Probability
Lines and Angles
- Introduction to Lines and Angles
- Basic Terms and Definitions
- Intersecting Lines and Non-intersecting Lines
- Introduction to Parallel Lines
- Pairs of Angles
- Parallel Lines and a Transversal
- Angle Sum Property of a Triangle
Triangles
- Concept of Triangles
- Congruence of Triangles
- Criteria for Congruence of Triangles
- Properties of a Triangle
- Some More Criteria for Congruence of Triangles
- Inequalities in a Triangle
Quadrilaterals
- Concept of Quadrilaterals
- Properties of a Quadrilateral
- Types of Quadrilaterals
- Another Condition for a Quadrilateral to Be a Parallelogram
- Theorem of Midpoints of Two Sides of a Triangle
- Property: The Opposite Sides of a Parallelogram Are of Equal Length.
- Theorem: A Diagonal of a Parallelogram Divides It into Two Congruent Triangles.
- Theorem : If Each Pair of Opposite Sides of a Quadrilateral is Equal, Then It is a Parallelogram.
- Property: The Opposite Angles of a Parallelogram Are of Equal Measure.
- Theorem: If in a Quadrilateral, Each Pair of Opposite Angles is Equal, Then It is a Parallelogram.
- Property: The diagonals of a parallelogram bisect each other. (at the point of their intersection)
- Theorem : If the Diagonals of a Quadrilateral Bisect Each Other, Then It is a Parallelogram
Circles
Areas - Heron’S Formula
Surface Areas and Volumes
Statistics
Algebraic Expressions
Algebraic Identities
Area
Constructions
- Introduction of Constructions
- Basic Constructions
- Some Constructions of Triangles
Probability
Notes
The likelihood of something happening is called the probability.
Terms related to probability:
Experiment : An activity which produces an outcome or result is called an experiment.
random Experiment : An Experiment in which exact outcome cannot be predicted in advance.
For example:
1) rolling a dice
2) Drawing a card from well-shuffled pack of playing cards
3) Tossing a coin
Trial : Performing an experiment is called a trial.
Event : Each possible outcomes of an experiment is called event.
Probability of an event : In a random experiment if 'n' is the total number of trials, then the empirical probability of the event E is P(E).
P(E) =
`"Number of trials happened in which event happened" / " Total number of trials"`
i.e. P(E) =`"Number of trials happened in which event happened" / n `
The Probability of an event lies between 0 and 1 (0 and 1 inclusive).
Shaalaa.com | Probability Experimental Approach
Related QuestionsVIEW ALL [67]
A company selected 4000 households at random and surveyed them to find out a relationship between income level and the number of television sets in a home. The information so obtained is listed in the following table:
| Monthly income (in Rs) |
Number of Television/household | |||
| 0 | 1 | 2 | Above 2 | |
| < 10000 | 20 | 80 | 10 | 0 |
| 10000 – 14999 | 10 | 240 | 60 | 0 |
| 15000 – 19999 | 0 | 380 | 120 | 30 |
| 20000 – 24999 | 0 | 520 | 370 | 80 |
| 25000 and above | 0 | 1100 | 760 | 220 |
Find the probability of a household not having any television.
80 bulbs are selected at random from a lot and their life time (in hrs) is recorded in the form of a frequency table given below:
| Life time (in hours) | 300 | 500 | 700 | 900 | 1100 |
| Frequency | 10 | 12 | 23 | 25 | 10 |
One bulb is selected at random from the lot. The probability that its life is 1150 hours, is
Bulbs are packed in cartons each containing 40 bulbs. Seven hundred cartons were examined for defective bulbs and the results are given in the following table:
| Number of defective bulbs | 0 | 1 | 2 | 3 | 4 | 5 | 6 | more than 6 |
| Frequency | 400 | 180 | 48 | 41 | 18 | 8 | 3 | 2 |
One carton was selected at random. What is the probability that it has
- no defective bulb?
- defective bulbs from 2 to 6?
- defective bulbs less than 4?
Over the past 200 working days, the number of defective parts produced by a machine is given in the following table:
| Number of defective parts |
0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 |
| Days | 50 | 32 | 22 | 18 | 12 | 12 | 10 | 10 | 10 | 8 | 6 | 6 | 2 | 2 |
Determine the probability that tomorrow’s output will have not more than 5 defective parts
The distance (in km) of 40 engineers from their residence to their place of work were found as follows.
| 5 | 3 | 10 | 20 | 25 | 11 | 13 | 7 | 12 | 31 |
| 19 | 10 | 12 | 17 | 18 | 11 | 32 | 17 | 16 | 2 |
| 7 | 9 | 7 | 8 | 3 | 5 | 12 | 15 | 18 | 3 |
| 12 | 14 | 2 | 9 | 6 | 15 | 15 | 7 | 6 | 12 |
What is the empirical probability that an engineer lives:-
(i) less than 7 km from her place of work?What is the empirical probability that an engineer lives:
(ii) more than or equal to 7 km from her place of work?
(iii) within 1/2 km from her place of work?
