# Introduction

A brief history of how probability was developed within the discipline of mathematics. Random processes can be modelled or explained mathematically by using a probability model. The two probability models are a) Experimental approach to probability b) Theoretical approach to probability. The basic principle of counting is covered.

In everyday life, we come across statements such as

1. It will probably rain today.
2. I doubt that he will pass the test.
3. Most probably, Kavita will stand first in the annual examination.
4. Chances are high that the prices of diesel will go up.
5. There is a 50-50 chance of India winning a toss in today’s match.

The words ‘probably’, ‘doubt’, ‘most probably’, ‘chances’, etc., used in the statements above involve an element of uncertainty. For example, in (1), ‘probably rain’ will mean it may rain or may not rain today. We are predicting rain today based on our past experience when it rained under similar conditions. Similar predictions are also made in other cases listed in (2) to (5).

The uncertainty of ‘probably’ etc. can be measured numerically by means of ‘probability’ in many cases. Though probability started with gambling, it has been used extensively in the fields of Physical Sciences, Commerce, Biological Sciences, Medical Sciences, WeatherForecasting,etc.

Probability theory like many other branches of mathematics, evolved out of practical consideration. It had its origin in the 16th century when an Italian physician and mathematician Jerome Cardan (1501–1576) wrote the first book on the subject “Book on Games of Chance” (Biber de Ludo Aleae). It was published in 1663 after his death.

When something occurs it is called an event. For example : A spinner has 4 equal sectors coloured yellow, blue, green and red. What are the chances of landing on blue after spinning the spinner? What are the chances of landing on red? The chances of landing on blue are 1 in 4, or one fourth. The chances of landing on red are 1 in 4, or one fourth.

An experiment is a situation involving chance or probability that leads to results called outcomes. In the problem above, the experiment is spinning the spinner.

An outcome is the result of a single trial of an experiment. The possible outcomes are landing on yellow, blue, green or red.

An event is one or more outcomes of an experiment. One event of this experiment is landing on blue.

Probability is the measure of how likely an event is. The probability of landing on blue is one fourth.

Impossible Event is an event that can never occur. The probability of landing on purple after spinning the spinner is impossible as it is impossible to land on purple since the spinner does not contain this colour.

Certain events: That the event will surely occur. If we consider the situation where A teacher chooses a student at random from a class of 30 girls. What is the probability that the student chosen is a girl? Since all the students in the class are girls, the teacher is certain to choose a girl.

## Historical Note

In 1654, a gambler Chevalier de Metre approached the well known French Philosoher and Mathematician Blaise Pascal (1623–1662) for certain dice problem. Pascal became interested in these problems and discussed with famous French Mathematician Pierre de Fermat (1601–1665). Both Pascal and Fermat solved the problem independently. Besides, Pascal and Fermat, outstanding contributions to probability theory were also made by Christian Huygenes (1629–1665), a Dutchman, J. Bernoulli (1654–1705), De Moivre (1667–1754), a Frenchman Pierre Laplace (1749–1827), A Frenchman and the Russian P.L Chebyshev (1821–1897), A. A Markov (1856–1922) and A. N Kolmogorove (1903–1987). Kolmogorove is credited with the axiomatic theory of probability. His book ‘Foundations of Probability’ published in 1933, introduces probability as a set function and is considered a classic.

## Experimental & Theoretical Approach

A Random Experiment is an experiment, trial, or observation that can be repeated numerous times under the same conditions. The outcome of an individual random experiment must be independent and identically distributed. It must in no way be affected by any previous outcome and cannot be predicted with certainty.

Examples of a Random experiment include: The tossing of a coin. The experiment can yield two possible outcomes, heads or tails. The roll of a die. The experiment can yield six possible outcomes, this outcome is the number 1 to 6 as the die faces are labelled.

A complete list of all possible outcomes of a random experiment is called sample space or possibility space and is denoted by S

# Textbook

Karnataka text book for Class 10, Chapter 05-Probability

# Teaching Outlines

## Concept #1 Introduction to Probability

### Learning objectives

1. Understand that events occur with different frequencies
2. Different events have different likelihoods (likely, unlikely, equally likely, not equally likely)
3. Understand the idea of sample space and universe of events

### Notes for teachers

1. To understand likelihood of events happening
2. The objective here is not numerical computation but to understand events, likelihoods and vocabulary of description. The activity can be done in groups/ pairs. Not a whole class activity.
3. Compare the results across groups.
4. To develop an understanding of what chance means?

### Activities

1. Activity No #1 probability_introduction_activity1
2. Activity No #2 probability_introduction_activity2

## Concept #2 Different types of events

### Learning objectives

1. Understand elementary and compound events and construction of such events
1. Complementary events
2. Independent events / Mutually exclusive events

### Activities

1. Activity No #1 probability_types_of_events_activity1
2. Activity No #2 probability_types_of_events_activity2

## Concept #3 Conditional probability

### Activities

1. Activity No #1 Concept Name - Activity No.
2. Activity No #2 Concept Name - Activity No.