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Experimental Probability – Formula, Definition With Examples

Camille Ira Mendoza

January 12, 2024

12 minutes read

Welcome to another exciting journey with us at Brighterly, where we make the learning of complex mathematical concepts a fun and engaging process. Today, we embark on a venture into the world of experimental probability, a vital aspect of mathematics that breathes life into numbers through practical, real-world experiences. But what exactly is experimental probability, and how does it differ from theoretical probability? How can we calculate experimental probability, and how is it applicable in our everyday lives? This article aims to answer these questions and more, unraveling the mysteries of experimental probability in an easy-to-understand and approachable manner.

Our trip into the world of experimental probability will cover the core concepts, definitions, and the all-important formula that underpins this fascinating area of mathematics. We’ll take a step back to appreciate the broader context of probability before focusing our lens on experimental probability, understanding its properties and contrasts with theoretical probability. With plenty of examples and practice problems, you’ll have a firm grasp on experimental probability, ready to see and use it in the world around you!

What Is Experimental Probability?

Probability, as a field of mathematics, often focuses on predicting the likelihood of certain events. However, it’s important to note that there are two main types of probability: theoretical and experimental. In this article, we will zero in on experimental probability.

Experimental probability, also known as empirical probability, is all about actual experiments and real-world observations. The main idea behind experimental probability is that it calculates the chances of an event happening based on the actual results of an experiment. This method of calculation is particularly interesting because it revolves around practical events that have already occurred, rather than theoretical or hypothetical situations.

In experimental probability, we conduct a certain experiment multiple times and observe the number of times a specific event occurs. This might sound quite complex, but we’ll dive into this concept with a greater depth in the upcoming sections, making it easily understandable.

Definition of Probability

Before we delve into experimental probability, let’s take a step back and understand the basic concept of probability. Probability is defined as a branch of mathematics that measures the likelihood of events to occur. It’s expressed as a number between 0 and 1, where 0 indicates impossibility and 1 signifies certainty.

For example, consider flipping a fair coin. The probability of landing a “heads” is 1 out of 2, or 0.5, meaning there’s a 50% chance to get a “heads”. The same applies to “tails”.

Understanding probability can help us make predictions about the outcomes of a random event and aids in making informed decisions in various aspects of life including gaming, statistics, and even weather forecasting.

Definition of Experimental Probability

Moving on to experimental probability, it is defined as the ratio of the number of times an event occurs to the total number of trials or times the activity is performed. The experimental probability of an event is calculated by conducting an experiment and recording the results.

For instance, let’s say we roll a dice 100 times, and the number “4” comes up 15 times. Here, the experimental probability of rolling a “4” would be the number of successful outcomes (rolling a “4”) divided by the total number of outcomes (total dice rolls), or 15/100 = 0.15.

In other words, experimental probability is the actual probability obtained from the direct observation or testing during an experiment. Unlike theoretical probability, it doesn’t rely on the inherent nature of the experiment, but rather on the actual data collected.

Properties of Probability

Understanding the properties of probability can provide us with insights about how probability functions. Here are some of the essential properties:

1. The probability of an event ranges from 0 to 1.
2. The sum of probabilities of all possible outcomes is always 1.
3. The probability of the complement of an event (an event not happening) is 1 minus the probability of the event.
4. If two events are mutually exclusive (they can’t occur at the same time), the probability of either event occurring is the sum of their individual probabilities.

These properties provide a foundational understanding of how probability works, whether it’s theoretical or experimental probability.

Properties of Experimental Probability

The properties of experimental probability are closely tied to those of theoretical probability, but with an emphasis on the data collected through experimentation. Here are the primary properties:

1. Experimental probability also ranges from 0 to 1. An experimental probability of 0 means the event never happened in the experiment, and a probability of 1 means the event always occurred.
2. As more trials are conducted, the experimental probability tends to approach the theoretical probability, given that the experiment is unbiased. This is known as the law of large numbers.
3. Like in theoretical probability, the sum of experimental probabilities of all possible outcomes is 1.

Understanding these properties can greatly aid in interpreting the results of experiments and the likelihood of outcomes.

Difference Between Theoretical and Experimental Probability

The primary difference between theoretical and experimental probability lies in their calculation and interpretation. Theoretical probability is based on the possible outcomes in theory. It assumes that all outcomes are equally likely, which isn’t always the case in real-world scenarios.

On the other hand, experimental probability is based on actual data collected from performed experiments. It deals with the frequency of occurrence of an event, providing a more empirical perspective on probability. For example, in theory, the probability of rolling a “6” on a fair die is 1/6. However, in an actual experiment of, say, 60 rolls, we might roll a “6” only 8 times. The experimental probability then becomes 8/60 or 0.1333.

Formula of Experimental Probability

The formula of experimental probability is quite straightforward:

Camille Ira Mendoza

I am a seasoned math tutor with over seven years of experience in the field. Holding a Master’s Degree in Education, I take great joy in nurturing young math enthusiasts, regardless of their age, grade, and skill level. Beyond teaching, I am passionate about spending time with my family, reading, and watching movies. My background also includes knowledge in child psychology, which aids in delivering personalized and effective teaching strategies.