# Experimental Probability

At first we will know the precise meaning of the term ‘experiment’ and the proper context in which it will be used in our experimental probability.

Definition of experiment: A process which can produce some well-defined results (outcomes) is called an experiment.

Some Experiments and their outcomes:

I. Tossing a coin:

Suppose we toss a coin and let it fall flat on the ground. Its upper face will show either Head (H) or Tail (T).

1. Whatever comes up, is called an outcome.

2. All possible outcomes are Head (H) and Tail (T).

II. Throwing a dice:

A dice is a solid cube having 6 faces, marked as 1, 2, 3, 4, 5, 6 respectively.
Suppose we throw a dice and let it fall flat on the ground. Its upper face will show one of the numbers 1, 2, 3, 4, 5, 6.

1. Whatever comes up, is called an outcome.
2. All possible outcomes are 1, 2, 3, 4, 5, 6.

The act of tossing a coin or throwing a dice is called an experiment.
Whatever comes up, is called an outcome.
In an experiment, all possible outcomes are known.

The plural of die is dice.

III. Drawing a card from a well-shuffled deck of 52 cards:

A deck of playing cards has in all 52 cards.

1. It has 13 cards each of four suits, namely spades, clubs, hearts and diamonds.

• Cards of spades and clubs are black cards.
• Cards of hearts and diamonds are red cards.

2. Kings, queens and jacks (or knaves) are known as face cards. Thus, there are 12 face cards in all.

Definition of Experimental Probability: The experimental probability of happening of an event is the ratio of the number of trials in which the event happened to the total number of trials.

The experimental probability of the occurrence of an event E is defined as:

Number of trials in which event happened
P(E) =                       Total number of trials

Solved examples on Experimental Probability:

1. Suppose we toss a coin 100 times and get a head 58 times. Now, we toss a coin at random. What is the probability of getting a head?

Solution:

Total number of trials = 100.
Number of times head appeared = 58.

Probability of getting a head =              Total number of trials

= 58/100

= 29/50

2. A coin is tossed 150 times and head is obtained 71 times. Now, if a coin is tossed at random, what is the probability of getting a tail?

Solution:

Total number of trials = 150.
Number of times head appeared = 71.
Number of times tail appeared = (150 - 71) = 79.

Number of times tail appeared
Probability of getting a tail =              Total number of trials

= 79/150

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

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The text passage provides definitions and examples related to experimental probability, including solved examples of calculating probabilities from coin tosses. It does not contain any new, unanswered mathematical questions.
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Given a text passage, determine:
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    2. If an answer to that mathematical question is provided in the text

First, describe the content structure you found in 1-2 sentences.

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system
# Experimental Probability

At first we will know the precise meaning of the term ‘experiment’ and the proper context in which it will be used in our experimental probability.

Definition of experiment: A process which can produce some well-defined results (outcomes) is called an experiment.

Some Experiments and their outcomes:

I. Tossing a coin:

Suppose we toss a coin and let it fall flat on the ground. Its upper face will show either Head (H) or Tail (T).

1. Whatever comes up, is called an outcome.

2. All possible outcomes are Head (H) and Tail (T).

II. Throwing a dice:

A dice is a solid cube having 6 faces, marked as 1, 2, 3, 4, 5, 6 respectively.
Suppose we throw a dice and let it fall flat on the ground. Its upper face will show one of the numbers 1, 2, 3, 4, 5, 6.

1. Whatever comes up, is called an outcome.
2. All possible outcomes are 1, 2, 3, 4, 5, 6.

The act of tossing a coin or throwing a dice is called an experiment.
Whatever comes up, is called an outcome.
In an experiment, all possible outcomes are known.

The plural of die is dice.

III. Drawing a card from a well-shuffled deck of 52 cards:

A deck of playing cards has in all 52 cards.

1. It has 13 cards each of four suits, namely spades, clubs, hearts and diamonds.

• Cards of spades and clubs are black cards.
• Cards of hearts and diamonds are red cards.

2. Kings, queens and jacks (or knaves) are known as face cards. Thus, there are 12 face cards in all.

Definition of Experimental Probability: The experimental probability of happening of an event is the ratio of the number of trials in which the event happened to the total number of trials.

The experimental probability of the occurrence of an event E is defined as:

Number of trials in which event happened
P(E) =                       Total number of trials

Solved examples on Experimental Probability:

1. Suppose we toss a coin 100 times and get a head 58 times. Now, we toss a coin at random. What is the probability of getting a head?

Solution:

Total number of trials = 100.
Number of times head appeared = 58.

Probability of getting a head =              Total number of trials

= 58/100

= 29/50

2. A coin is tossed 150 times and head is obtained 71 times. Now, if a coin is tossed at random, what is the probability of getting a tail?

Solution:

Total number of trials = 150.
Number of times head appeared = 71.
Number of times tail appeared = (150 - 71) = 79.

Number of times tail appeared
Probability of getting a tail =              Total number of trials

= 79/150

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

Didn't find what you were looking for? Or want to know more information about Math Only Math. Use this Google Search to find what you need.

## Recent Articles

1. ### Fraction in Lowest Terms |Reducing Fractions|Fraction in Simplest Form

Feb 28, 24 04:07 PM

There are two methods to reduce a given fraction to its simplest form, viz., H.C.F. Method and Prime Factorization Method. If numerator and denominator of a fraction have no common factor other than 1…

2. ### Equivalent Fractions | Fractions |Reduced to the Lowest Term |Examples

Feb 28, 24 01:43 PM

The fractions having the same value are called equivalent fractions. Their numerator and denominator can be different but, they represent the same part of a whole. We can see the shade portion with re…

3. ### Fraction as a Part of Collection | Pictures of Fraction | Fractional

Feb 27, 24 02:43 PM

How to find fraction as a part of collection? Let there be 14 rectangles forming a box or rectangle. Thus, it can be said that there is a collection of 14 rectangles, 2 rectangles in each row. If it i…

4. ### Fraction of a Whole Numbers | Fractional Number |Examples with Picture

Feb 24, 24 04:11 PM

Fraction of a whole numbers are explained here with 4 following examples. There are three shapes: (a) circle-shape (b) rectangle-shape and (c) square-shape. Each one is divided into 4 equal parts. One…
user
The text passage provides definitions and examples related to experimental probability, including solved examples of calculating probabilities from coin tosses. It does not contain any new, unanswered mathematical questions.

TYPE: NO_QUESTION