# Before giving a formal definition of probability, we explain some terms related to probability.

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1 probability 22 INTRODUCTION In our day-to-day life, we come across statements such as: (i) It may rain today. (ii) Probably Rajesh will top his class. (iii) I doubt she will pass the test. (iv) It is unlikely that India will win the world cup. (v) Chances are high that the prices of diesel will go up. The words may, probably, doubt, unlikely, chances used in the above statements indicate uncertainties. For example, in the statement (i), may rain today means 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 made in other cases listed (ii) to (v). is a measure of uncertainty. The theory of probability developed as a result of studies of game of chance or gambling. Suppose you pay ` 5 to throw a die if it comes up with number, you get ` 20, otherwise you get nothing. Should you play such a game? Does it give a fair chance of winning? Search for mathematical answers of these types of questions led to the development of modern theory of probability. Today, the probability is one of the basic tools of statistics and has wide range of applications in economics, biology, genetics, physics, sociology etc. 22. Before giving a formal definition of probability, we explain some terms related to probability. Some terms related to probability Experiment An action which results in some (well-defined) outcomes is called an experiment. Random experiment An experiment is called random if it has more than one possible outcome and it is not possible to tell (predict) the outcome in advance. Pierre Simon Laplace It is remarkable that a science, which began with the consideration of games of chance, should be elevated to the rank of the most important subject of human knowledge.

2 For example : (i) tossing a coin (ii) tossing two coins simultaneously (iii) throwing a die (iv) drawing a card from a pack of 52 (playing) cards. All these are random experiments. From now onwards, whenever the word experiment is used it will mean random experiment. Sample space The collection of all possible outcomes of an experiment is called sample space. Event A subset of the sample space associated with a random experiment is called an event. For example : (i) When a die is thrown, we can get any number, 2, 3, 4, 5, 6. So the sample space S = {, 2, 3, 4, 5, 6}. A few events of this experiment could be Getting a six : {6} Getting an even number : {2, 4, 6} Getting a prime number : {2, 3, 5} Getting a number less than 5 : {, 2, 3, 4}, etc. (ii) When a pair of coins is tossed, the sample space of the experiment S = {HH, HT, TH, TT}. A few events of this experiment could be Getting exactly one head : {HT, TH} Getting exactly two heads : {HH} Getting atleast one head : {HH, HT, TH}, etc. Occurrence of an event When the outcome of a random experiment satisfies the condition mentioned in the event, then we say that event has occurred. For example : (i) In the experiment of tossing a coin, an event E may be getting a head. If the coin comes up with head, then we say that event E has occurred, otherwise, if the coin comes up with tail, we say that event E has not occurred. (ii) In the experiment of tossing a pair of coins simultaneously, an event E may be getting two heads. If the pair of coins come up with two heads, then we say that event E has occurred, otherwise, we say that event E has not occurred. (iii) In the experiment of throwing a die, an event E may be taken as getting an even number. If the die comes up with any of the numbers 2, 4 or 6, we say that event E has occurred, otherwise, if the die comes up with, 3 or 5, we say that event E has not occurred. Favourable outcomes The outcomes which ensure the occurrence of an event are called favourable outcomes to that event. Equally likely outcomes If there is no reason for any one outcome to occur in preference to any other outcome, we say that the outcomes are equally likely. For example : (i) In tossing a coin, it is equally likely that the coin lands either head up or tail up. (ii) In throwing a die, each of the six numbers, 2, 3, 4, 5, 6 is equally likely to show up. 57

3 Are the outcomes of every experiment equally likely? Let us see. Suppose that a bag contains 5 red balls and blue ball, you draw a ball without looking into the bag. What are the outcomes? Are the outcomes a red ball or a blue ball equally likely? Since there are 5 red balls and only one blue ball, you would agree that you are more likely to get a red ball than that of a blue ball. So, the outcomes (a red ball or a blue ball) are not equally likely Definition of The assumption that all the outcomes are equally likely leads to the following definition of probability: of an event E, written as P (E), is defined as P (E) = number of outcomes favourable to E total number of possible outcomes. Let E be an event then the number of outcomes favourable to E is greater than or equal to zero and is less than or equal to total number of outcomes. It follows that 0 P(E). Sure event An event which always happens is called a sure event. For example, when we throw a die, then the event getting a number less than 7 is a sure event. The probability of a sure event is. Impossible event An event which never happens is called an impossible event. For example, when we throw a die, then the event getting a number greater than 6 is an impossible event. The probability of an impossible event is 0. Elementary event An event which has only one (favourable) outcome from the sample space is called an elementary event. The sum of the probabilities of all the elementary events of an experiment is. Compound event An event which has more than one (favourable) outcomes from the sample space is called a compound event. For example, when we throw a die, then the event getting number 5 i.e. {5} is an elementary event, whereas, the event getting an even number {2, 4, 6} is a compound event. Complementary event If E is an event, then the event not E is complementary event of E. For example, when we throw a die, let E be the event getting a number less than or equal to 2, then the event not E i.e. getting a number greater than 2 is complementary event of E. Complement of event E is denoted by e or E c or E. Let E be an event, then we have : (i) 0 P (E) 572 Understanding ICSE mathematics x (ii) P ( E ) = P (E) (iii) P (E) = P ( E ) (iv) P (E) + P( E ) =. now, we shall consider examples to find the probability for some of the events associated with random experiments where the assumption of equally likely outcomes hold.

4 Illustrative Examples Example. A coin is tossed once. Find the probability of getting (i) a head (ii) a tail. Solution. When a coin is tossed once, the possible outcomes are Head (H) and Tail (T). So, sample space = {H, T}. It consists of two equally likely outcomes. (i) Let E be the event of getting a head, then E = {H}. So, the number of favourable outcomes to E = P(E ) = number of favourable outcomes to e = total number of possible outcomes 2. (ii) Let E 2 be the event of getting a tail, then E 2 = {T}. So, the number of favourable outcomes to E 2 =. P(E 2 ) = number of favourable outcomes to e2 total number of possible outcomes = 2. note that E and E 2 are elementary events and P(E ) + P(E 2 ) = + =. 2 2 Thus, the sum of the probabilities of all the elementary events of an experiment =. Example 2. Gopi buys a fish from a shop for his aquarium. The shopkeeper takes out one fish at random from a tank containing 5 male fish and 8 female fish. What is the probability that the fish taken out is a male fish? Solution. As a fish is taken out at random from the tank, all the outcomes are equally likely. Total number of fish in the tank = = 3. Total number of possible outcomes = 3. Let E be the event taking out a male fish. As there are 5 male fish in the tank, the number of favourable outcomes to the event E = 5. P(E) = number of favourable outcomes to e total number of possible outcomes = 5 3. Example 3. A die is tossed once. Find the probability of getting (i) number 4 (ii) a number greater than 4 (iii) a number less than 4 (iv) an even number (v) a number greater than 6 (vi) a number less than 7 (vii) a multiple of 3 (viii) an even number or a multiple of 3 (ix) an even number and a multiple of 3. Solution. When a die is tossed once, the possible outcomes are the numbers, 2, 3, 4, 5, 6. So, the sample space of the experiment = {, 2, 3, 4, 5, 6}. It has six equally likely outcomes. (i) The event is getting the number 4 i.e. {4} The number of favourable outcomes to the event getting number 4 =. P (getting number 4) = 6. (ii) The event is getting a number greater than 4 and the outcomes greater than 4 are 5 and 6. So, the event is {5, 6} and the number of favourable outcomes to the event getting a number greater than 4 = 2 P (getting a number greater than 4) =

5 (iii) The event is getting a number less than 4 and the outcomes less than 4 are, 2, 3. So, the event is {, 2, 3} and the number of favourable outcomes to the event getting a number less than 4 = 3. P (getting a number less than 4) = (iv) The event is getting an even number and the even numbers (outcomes) are 2, 4, 6. So, the event is {2, 4, 6} and the number of favourable outcomes to the event getting an even number = 3. P (getting an even number) = (v) The event is getting a number greater than 6 and there is no outcome greater than 6. So, the event is ϕ and the number of favourable outcomes to the event getting a number greater than 6 = 0. P (getting a number greater than 6) = 0 6 = 0. note that in this experiment, getting a number greater than 6 is an impossible event. (vi) The event is getting a number less than 7 and all the outcomes, 2, 3, 4, 5, 6 are less than 7. So, the event is {, 2, 3, 4, 5, 6} and the number of favourable outcomes to the event getting a number less than 7 = 6. P (getting a number less than 7) = 6 6 =. note that in this experiment, getting a number less than 7 is a sure event. (vii) The event is getting a multiple of 3 and the outcomes which are multiples of 3 are 3 and 6. So, the event is {3, 6} and the number of favourable outcomes to the event getting a multiple of 3 = 2. P (getting a multiple of 3) = (viii) The event is getting an even number or a multiple 3 and the outcomes which are even numbers or a multiple of 3 are 2, 4, 6 and 3. So, the event is {2, 4, 6, 3} and the number of favourable outcomes to the event getting an even number or a multiple of 3 = 4. P (getting an even number or a multiple of 3) = (ix) The event is getting an even number and a multiple of 3 and the only outcome which is an even number and a multiple of 3 is 6. So, the event is {6} and the number of favourable outcomes to the event getting an even number and a multiple of 3 =. P (getting an even number and a multiple of 3) = 6. Example 4. A child has a die whose six faces show the letters as given below: A B C D E A The die is thrown once. What is probability of getting (i) A? (ii) D? Solution. When a die is thrown once, the sample space of the experiment has six equally likely outcomes A, B, C, D, E, A i.e. sample space = {A, B, C, D, E, A} (i) The outcomes favourable to the event getting A are A, A i.e. the event is {A, A} and the number of outcomes favourable to the event = 2 P (getting A) = Understanding ICSE mathematics x

6 (ii) Let the event be getting D i.e. {D}, so the number of outcomes favourable to the event = P (getting D) = 6. Example 5. If the probability of Sania winning a tennis match is 0 63, what is the probability of her losing the match? Solution. Let E be the event Sania winning the match, then P(E) = 0 63 (given). P (Sania losing the match) = P (not E) = P(E) = P(E) = 0 63 = 0 37 Note that winning the match and losing the match are complementary events. Example 6. Ankita and Nagma are friends. They were both born in 990. What is the probability that they have (i) same birthday? (ii) different birthdays? Solution. Note that the year 990 is a non-leap year. Out of two friends, say, Ankita s birthday can be any day of the 365 days in a (non-leap) year. Also Nagma s birthday can be any day of the 365 days of the same year. So, the total number of outcomes = 365. We assume that all these 365 outcomes are equally likely. (i) Let E be the event Ankita and Nagma have same birthday, then the number of favourable outcomes to the event E = P (E) = 365. (ii) P (Ankita and Nagma have different birthdays) = P (not E) = P(E) = P(E) 364 = Example 7. A box contains 5 red marbles, 8 white marbles and 4 green marbles. One marble is taken out of the box at random. Find the probability that the marble taken out is (i) red (ii) white (iii) green (iv) not green. Solution. Saying that a marble is taken out at random from the box means that all the marbles are equally likely to be drawn. Total number of marbles in the box = = 7. So, the sample space of the experiment has 7 equally likely outcomes. (i) Let R be the event the marble taken out is red. As there are 5 red marbles in the box, so the number of favourable outcomes to the event R = 5. 5 P(R) 7 (ii) Let W be the event, the marble taken out is white. As there are 8 white marbles in the box, so the number of favourable outcomes to the event W = 8. 8 P (W) 7 (iii) Let G be the event the marble taken out is green. As there are 4 green marbles in the box, so the number of favourable outcomes to the event G = 4. P (G) = 4 7. (iv) P (not green) = P (green) = 4 7 = 3 7. Alternatively The event marble taken out is not green means that the marble taken out is either red or white. The number of favourable outcomes to the event marble drawn is not green 575

7 P (not green) = 3 7. = number of red marbles + number of white marbles = = 3 Example 8. A bag contains 5 white balls, 6 red balls and 9 green balls. A ball is drawn at random from the bag. Find the probability that the ball drawn is : (i) a green ball (ii) a white or a red ball (iii) is neither a green ball nor a white ball. (205) Solution. Since a ball is drawn at random from the bag, so all the balls are equally likely to be drawn. Total number of balls in the bag = = 20. So, the sample space of the experiment has 20 equally likely outcomes. (i) Let E be the event a green ball is drawn. As there are 9 green balls in the bag, so the number of favourable outcomes to event E = 9 9 P (E ) = P (a green ball) = 20. (ii) Let E 2 be the event a white or a red ball is drawn. The number of white balls or red balls = =. So, the number of favourable outcomes to the event E 2 =. P (E 2 ) = P (a white or a red ball) = 20. (iii) Let E 3 be the event neither a green ball nor a white ball means a red ball. The number of ball which are neither green nor white = the number of red balls = 6. So, the number of favourable outcomes to the event E 3 = 6. 6 P (E 3 ) = P (neither a green ball nor a white ball) = 20 = 3 0. Example 9. If 65% of the population have black eyes, 25% have brown eyes and the remaining have blue eyes, what is the probability that a person selected at random has (i) blue eyes (ii) brown or black eyes (iii) neither blue nor brown eyes? Solution. Given 65% of the population have black eyes, 25% have brown eyes and the remaining i.e. ( )% i.e. 0% have blue eyes. Let the total number of people be 00, then 65 have black eyes, 25 have brown eyes and 0 have blue eyes. Thus, the sample space of the experiment has 00 equally likely outcomes. (i) Let the event be have blue eyes. As 0 people have blue eyes, so the number of favourable outcomes to the event have blue eyes = 0. P (blue eyes) = (ii) Let the event be have brown or black eyes. The number of persons who have brown or black eyes = = 90. So, the number of favourable outcomes to the event have brown or black eyes = 90. P (brown or black eyes) = (iii) The event have neither blue nor brown eyes mean have black eyes. The number of persons who have neither blue nor brown eyes = number of persons who have black eyes = 65. So, the number of favourable outcomes to the event have neither blue nor brown eyes = Understanding ICSE mathematics x

8 65 3 P(neither blue nor brown eyes) = Example 0. A child s game has 8 triangles of which 3 are blue and rest are red, and 0 squares of which 6 are blue and rest are red. One piece is lost at random. Find the probability that it is a (i) triangle (ii) square (iii) square of blue colour (iv) triangle of red colour. Solution. A child s game has 8 triangular pieces and 0 squared pieces. So, total number of pieces in the game = = 8. One piece is lost at random means that all pieces are equally likely to be lost. Therefore, the sample space of the experiment has 8 equally likely outcomes. (i) Number of triangular pieces = P (triangle) = 8 9 (ii) Number of squared pieces = 0. P (square) = (iii) Number of blue squared pieces = 6. 6 P (square of blue colour) = 8 3 (iv) Number of red coloured triangular pieces = total number of triangular pieces blue coloured triangular pieces = 8 3 = 5 5 P (triangle of red colour) = 8. Example. A game of numbers has cards marked with, 2, 3,, 40. A card is drawn at random. Find the probability that the number on the card drawn is : (i) a perfect square. (ii) divisible by 7. (206) Solution. A card is drawn at random means that all the outcomes are equally likely. As the cards are marked with numbers, 2, 3,, 40, the total number of cards = 30. Sample space = {, 2, 30,, 40} and it has 30 equally likely outcomes. (i) Let E be the event a perfect square number. The numbers from to 40 which are perfect squares are 6, 25, 36. So, E = {6, 25, 36} and the number of favourable outcomes to E = 3. 3 P(E) = 30 0 (ii) Let F the event divisible by 7. The numbers from to 40 which are divisible by 7 are 4, 2, 28, 35. So, F = {4, 2, 28, 35} and the number of favourable outcomes to F = P (F) = 30 5 Example 2. A box contains 7 cards numbered, 2, 3,..., 7 and are mixed thoroughly. A card is drawn at random from the box. Find the probability that the number on the card is (i) odd (ii) even (iii) prime (iv) divisible by 3 (v) divisible by 3 and 2 both (vi) divisible by 3 or 2. Solution. The cards are mixed thoroughly and a card is drawn at random from the box means that all the outcomes are equally likely. 577

9 Sample space = {, 2, 3,, 7}, which has 7 equally likely outcomes. (i) Let A be the event the number on the card drawn is odd, then A = {, 3, 5, 7, 9,, 3, 5, 7}. The number of favourable outcomes to the event A = 9. 9 P (odd) 7 (ii) Let B be the event the number on the card drawn is even, then B = {2, 4, 6, 8, 0, 2, 4, 6}. The number of favourable outcomes to the event B = 8. 8 P (even) 7 (iii) Let C be the event the number on the card drawn is prime, then C = {2, 3, 5, 7,, 3, 7}. The number of favourable outcomes to the event C = 7. 7 P (prime) 7 (iv) Let D be the event the number on the card is divisible by 3, then d = {3, 6, 9, 2, 5}. The number of favourable outcomes to the event D = 5. 5 P (divisible by 3) 7 (v) Let E be the event the number on the card drawn is divisible by 3 and 2 both, then E = {6, 2}. The number of favourable outcomes to the event E = 2. 2 P (divisible by 3 and 2 both) 7 (vi) Let F be the event be the number on the card drawn is divisible by 3 or 2, then F = {2, 3, 4, 6, 8, 9, 0, 2, 4, 5, 6}. The number of favourable outcomes to the event F =. P (divisible by 3 or 2) = 7. Example 3. Cards marked with all 2-digit numbers are placed in a box and are mixed thoroughly. One card is drawn at random. Find the probability that the number on the card is (i) divisible by 0 (ii) a perfect square number (iii) a prime number less than 25. Solution. Cards have numbers 0 to 99 (both inclusive). So, sample space S = {0,, 2,, 99}. Total number of cards in the box = 90 (99 9) The sample space has 90 equally likely outcomes. (i) The numbers from 0 to 99 which are divisible by 0 are 0, 20, 30,, 90. So, the event divisible by 0 = {0, 20, 30,, 90} and the number of favourable outcomes to the event divisible by 0 = 9. 9 P (divisible by 0) = 90 0 (ii) The numbers from 0 to 99 which are perfect squares are 6, 25, 36, 49, 64, 8. So, the event a perfect square number = {6, 25, 36, 49, 64, 8} and the number of favourable outcomes to the event a perfect square number = Understanding ICSE mathematics x

10 P (a perfect square number) = (iii) The numbers from 0 to 99 which are prime numbers and less than 25 are, 3, 7, 9, 23. So, the event a prime number less than 25 = {, 3, 7, 9, 23} and the number of outcomes favourable to this event = 5. 5 P (a prime number less than 25) = 90 8 Example 4. Find the probability of having 53 Sundays in (i) a non-leap year (ii) a leap year. Solution. (i) In non-leap year, there are 365 days and 364 days make 52 weeks. Therefore, we have to find the probability of having a Sunday out of the remaining day. Hence, probability (having 53 Sundays) = 7. (ii) In a leap year, there are 366 days and 364 days make 52 weeks and in each week there is one Sunday. Therefore, we have to find the probability of having a Sunday out of the remaining 2 days. now the 2 days can be (Sunday, Monday) or (Monday, Tuesday) or (Tuesday, Wednesday) or (Wednesday, Thursday) or (Thursday, Friday) or (Friday, Saturday) or (Saturday, Sunday). Note that Sunday occurs 2 times in these 7 pairs. Let the event be having a Sunday, then the number of favourable outcomes to the event = 2. (having 53 Sundays) = 2 7. Example 5. A jar contains 24 marbles, some are green and others are blue. If a marble is drawn at random from the jar, the probability that it is green is 2 Find the number of blue marbles 3 in the jar. Solution. As a marble is drawn at random from a jar containing 24 marbles, so the sample space has 24 equally likely outcomes. Let the jar contain x green marbles, then x 2 P (a green marble) = = (given) x = 48 x = 6. The number of blue marbles in the jar = 24 6 = 8. Example 6. A box contains 50 apples. If one apple is taken out from the box at random and the probability of its being rotten is 0 06, then find the number of good apples in the box. Solution. A box contains 50 apples and one apple is taken out at random, so the sample space has 50 equally likely outcomes. Let the box contain x rotten apples, then x P (rotten apple) = = 0 06 (given) 50 x = = 9. The number of good apples in the box = 50 9 = 4. Example 7. A box contains some black balls and 30 white balls. If the probability of drawing a black ball is two-fifths of a white ball, find the number of black balls in the box. (203) Solution. Let the number of black balls in the box be x. Then the total number of balls in the box = x As a ball is drawn at random, all outcomes are equally likely. 579

11 The probability of drawing a black ball = the probability of drawing a white ball = According to given, x 2 30 = x x + 30 x x x + 30 x = 2. Hence, the number of black balls in the box = 2. and Example 8. A bag contains 2 balls out of which x are black. (i) If a ball is drawn at random, what is the probability that it will be a black ball? (ii) If 6 more black balls are put in the bag, the probability of drawing a black ball will be double than that of (i). Find the value of x. Solution. All outcomes are equally likely. (i) Total number of outcomes = 2. Let the event be drawing a black ball, then the number of favourable outcome to the event = x. x P (drawing a black ball) 2 (ii) Now, 6 more black balls are put in the bag. Total number of balls in the bag = = 8. number of black balls in the bag become x + 6. Let the event be drawing a black ball, then the number of favourable outcomes to the event = x + 6. P (drawing a black ball) = x According to the question, x = 2 x + 6 = 3x 2x = 6 x = 3 Hence, the value of x is 3. A Note on a Pack of 52 Cards You must have seen a pack or (deck) of playing cards. It consists of 52 cards which are divided into 4 suits of 3 cards each spades ( ), hearts ( ), diamonds ( ) and clubs ( ). Spades and clubs are of black colour, while hearts and diamonds are of red colour. The cards in each suit are ace, king, queen, jack, 0, 9, 8, 7, 6, 5, 4, 3 and 2. Kings, queens and jacks are called face (or picture or court) cards. The cards bearing numbers 0, 9, 8, 7, 6, 5, 4, 3 and 2 are called numbered cards. Thus a pack of playing cards has 4 aces, 2 face cards and 36 numbered cards. The aces together with face cards i.e. aces, kings, queens and jacks are called cards of honour; so there are 6 cards of honour. x 2 Example 9. A card is drawn from a well-shuffled deck of 52 cards. Find the probability that the card drawn is : (i) an ace (ii) a red card (iii) neither a king nor a queen (iv) a face card (v) a card of spade or an ace (vi) non-face card of red colour. Solution. Well-shuffling ensures equally likely outcomes. Total number of outcomes = Understanding ICSE mathematics x

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