Using an experimental probability is just as accurate as using the theoretical probability.
True or False?
False.
To understand why the statement is false, we need to first understand what experimental probability and theoretical probability mean.
Theoretical probability is calculated by using mathematical principles and assumptions. It is determined by dividing the number of desired outcomes by the total number of possible outcomes. Given a set of favorable outcomes and knowing all the possible outcomes of the event, we can calculate the theoretical probability.
On the other hand, experimental probability is determined by conducting experiments or observations and collecting data. It involves conducting an actual experiment or observing a real-world scenario multiple times to determine the likelihood of an event occurring.
The key difference between the two lies in their accuracy. Theoretical probability is considered to be more accurate because it is based on mathematical calculations and assumptions. It provides a precise understanding of the likelihood of an event occurring given that all the assumptions hold true.
On the contrary, experimental probability is subject to variability and can be influenced by the specific conditions in which the experiment or observation is conducted. It relies on real-world data, which may introduce errors or biases due to limitations in the sample size, selection bias, or other factors. Therefore, experimental probabilities are generally considered less accurate than theoretical probabilities.
Hence, it is not true to say that using experimental probability is just as accurate as using theoretical probability. Theoretical probability provides a more precise estimation based on mathematical principles, while experimental probability is subject to the limitations and variability of real-world observations and experiments.