# Coin Toss Probability

Problems on coin toss probability are explained here with different examples.

When we flip a coin there is always a probability to get a head or a tail is 50 percent.

Suppose a coin tossed then we get two possible outcomes either a ‘head’ (H) or a ‘tail’ (T), and it is impossible to predict whether the result of a toss will be a ‘head’ or ‘tail’.

The probability for equally likely outcomes in an event is:

Number of favourable outcomes ÷ Total number of possible outcomes

Total number of possible outcomes = 2

(i) If the favourable outcome is head (H).

Number of favourable outcomes = 1.

Number of favorable outcomes
= P(H) =   total number of possible outcomes

= 1/2.

(ii) If the favourable outcome is tail (T).

Number of favourable outcomes = 1.

Therefore, P(getting a tail)

Number of favorable outcomes
= P(T) =   total number of possible outcomes

= 1/2.

Word Problems on Coin Toss Probability:

1. A coin is tossed twice at random. What is the probability of getting

(ii) the same face?

Solution:

The possible outcomes are HH, HT, TH, TT.

So, total number of outcomes = 4.

(i) Number of favourable outcomes for event E

= Number of outcomes having at least one head

= 3 (as HH, HT, TH are having at least one head).

So, by definition, P(F) = $$\frac{3}{4}$$.

(ii) Number of favourable outcomes for event E

= Number of outcomes having the same face

= 2 (as HH, TT are have the same face).

So, by definition, P(F) = $$\frac{2}{4}$$ = $$\frac{1}{2}$$.

2. If three fair coins are tossed randomly 175 times and it is found that three heads appeared 21 times, two heads appeared 56 times, one head appeared 63 times and zero head appeared 35 times.

What is the probability of getting

Solution:

Total number of trials = 175.

Number of times three heads appeared = 21.

Number of times two heads appeared = 56.

Number of times one head appeared = 63.

Number of times zero head appeared = 35.

Number of times three heads appeared
= P(E1) =             total number of trials

= 21/175

= 0.12

Number of times two heads appeared
= P(E2) =             total number of trials

= 56/175

= 0.32

Number of times one head appeared
= P(E3) =             total number of trials

= 63/175

= 0.36

Number of times zero head appeared
= P(E4) =             total number of trials

= 35/175

= 0.20

Note: Remember when 3 coins are tossed randomly, the only possible outcomes

are E2, E3, E4 and

P(E1) + P(E2) + P(E3) + P(E4)

= (0.12 + 0.32 + 0.36 + 0.20)

= 1

3. Two coins are tossed randomly 120 times and it is found that two tails appeared 60 times, one tail appeared 48 times and no tail appeared 12 times.

If two coins are tossed at random, what is the probability of getting

(i) 2 tails,

(ii) 1 tail,

(iii) 0 tail

Solution:

Total number of trials = 120

Number of times 2 tails appear = 60

Number of times 1 tail appears = 48

Number of times 0 tail appears = 12

Let E1, E2 and E3 be the events of getting 2 tails, 1 tail and 0 tail respectively.

(i) P(getting 2 tails)

Number of times 2 tails appear
= P(E1) =       total number of trials

= 60/120

= 0.50

(ii) P(getting 1 tail)

Number of times 1 tail appear
= P(E2) =       total number of trials

= 48/120

= 0.40

(iii) P(getting 0 tail)

Number of times no tail appear
= P(E3) =       total number of trials

= 12/120

= 0.10

Note:

Remember while tossing 2 coins simultaneously, the only possible outcomes are E1, E2, E3 and,

P(E1) + P(E2) + P(E3)

= (0.50 + 0.40 + 0.10)

= 1

4. Suppose a fair coin is randomly tossed for 75 times and it is found that head turns up 45 times and tail 30 times. What is the probability of getting (i) a head and (ii) a tail?

Solution:

Total number of trials = 75.

Number of times head turns up = 45

Number of times tail turns up = 30

(i) Let X be the event of getting a head.

Number of times head turns up
= P(X) =       total number of trials

= 45/75

= 0.60

(ii) Let Y be the event of getting a tail.

P(getting a tail)

Number of times tail turns up
= P(Y) =       total number of trials

= 30/75

= 0.40

Note: Remember when a fair coin is tossed and then X and Y are the only possible outcomes, and

P(X) + P(Y)

= (0.60 + 0.40)

= 1

## You might like these

• ### Theoretical Probability |Classical or A Priori Probability |Definition

Moving forward to the theoretical probability which is also known as classical probability or priori probability we will first discuss about collecting all possible outcomes and equally likely outcome. When an experiment is done at random we can collect all possible outcomes

In 10th grade worksheet on probability we will practice various types of problems based on definition of probability and the theoretical probability or classical probability. 1. Write down the total number of possible outcomes when the ball is drawn from a bag containing 5

• ### Probability |Terms Related to Probability|Tossing a Coin|Coin Probabil

Probability in everyday life, we come across statements such as: Most probably it will rain today. Chances are high that the prices of petrol will go up. I doubt that he will win the race. The words ‘most probably’, ‘chances’, ‘doubt’ etc., show the probability of occurrence

• ### Worksheet on Playing Cards | Playing Cards Probability | With Answers

In math worksheet on playing cards we will solve various types of practice probability questions to find the probability when a card is drawn from a pack of 52 cards. 1. Write down the total number of possible outcomes when a card is drawn from a pack of 52 cards.

• ### Rolling Dice Probability Worksheet |Dice Probability Worksheet|Answers

Practice different types of rolling dice probability questions like probability of rolling a die, probability for rolling two dice simultaneously and probability for rolling three dice simultaneously in rolling dice probability worksheet. 1. A die is thrown 350 times and the

Probability

Probability

Random Experiments

Experimental Probability

Empirical Probability

Coin Toss Probability

Probability of Tossing Two Coins

Probability of Tossing Three Coins

Complimentary Events

Mutually Exclusive Events

Mutually Non-Exclusive Events

Conditional Probability

Theoretical Probability

Odds and Probability

Playing Cards Probability

Probability and Playing Cards

Solved Probability Problems

Probability for Rolling Three Dice