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In probability, equally likely events refer to outcomes that have the same chance of occurring. Imagine a scenario where you have a fair die. Rolling any of the six numbers (1 through 6) has an equal probability because the die is not biased. In our exercise, we're dealing with days of the week when a baby could be born. Since there are 7 days available, and assuming no external factors affecting the birth day, each day (Monday through Sunday) is equally probable. This gives each day a probability of \( \frac{1}{7} \).

When talking about equally likely events, it's important to affirm that each event must always have precisely the same chance of happening for them to be considered equal. Real-life situations often rely on this principle for simplifying complex problems.

Equally likely events make calculations more manageable because of their uniform probability, allowing us to directly use these values in further probability rules.

Disjoint events, also known as mutually exclusive events, are events that cannot occur simultaneously. In simpler terms, if one event happens, the other cannot happen at the same time. This concept is embodied in our exercise with the days of birth. A baby cannot be born on both Friday and Saturday simultaneously; these events are separate with no overlap.

Understanding disjoint events helps us simplify probability calculations. When events are disjoint, the total probability of any of these events occurring is just the sum of their individual probabilities. Always remember, for events to be considered disjoint, their occurrence must be mutually exclusive, meaning they do not affect each other and cannot happen at the same time.

The probability addition rule is a fundamental concept used to find the probability of any one of several mutually exclusive events happening. This rule simplifies the addition of probabilities for disjoint events, which is exactly what we employed in our exercise.

For disjoint events, the probability addition rule states: if you want to find the probability of one event OR another event occurring, you simply add the probabilities of each event together. Mathematically, for two disjoint events \( A \) and \( B \), the probability \( P(A \text{ or } B) = P(A) + P(B) \).

In our exercise, this is evident as we looked for the probability of a baby being born on either Friday, Saturday, or Sunday. Using the rule, we added the probabilities directly: \( \frac{1}{7} + \frac{1}{7} + \frac{1}{7} = \frac{3}{7} \). This illustrates how the rule functions effectively for determining probabilities involving multiple disjoint events, making computations straightforward and intuitive.