Understanding Experimental Probability | Definition, Calculation, and Importance.

Experimental Probability

Experimental probability, also known as empirical probability or observed probability, is a measure of the likelihood of an event based on the outcomes of a real-world experiment or observation

Experimental probability, also known as empirical probability or observed probability, is a measure of the likelihood of an event based on the outcomes of a real-world experiment or observation. It is determined by conducting experiments and recording the outcomes, then calculating the ratio of the number of times the event occurred to the total number of trials.

To understand experimental probability, let’s consider an example. Suppose you want to find the experimental probability of flipping a coin and getting heads. You decide to flip the coin 100 times and record the outcomes. After completing the experiment, you find that the coin landed on heads 58 times.

To calculate the experimental probability, you divide the number of successful outcomes (getting heads) by the total number of trials (flips):

Experimental Probability = Number of Heads / Total Number of Trials

In this case, the experimental probability of getting heads would be:

Experimental Probability = 58 / 100 = 0.58 or 58%

So, based on the experiment, the probability of flipping a coin and getting heads is approximately 0.58 or 58%.

It is important to note that experimental probability can vary because it is based on the outcomes of a finite number of trials. This is in contrast to theoretical probability, which is based on mathematical calculations and assumes an infinite number of trials. The experimental probability tends to approach the theoretical probability as the number of trials increases.

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