Visual Guide: - These are the probabilities of the initial weather events. They are mutually exclusive and sum to $1.0$. Why this matters: - Every branches group from a single node represents all possible outcomes. Therefore, their sum must always equal $1.0$ ($100\%$ probability).

Concept: - **Conditional Probability ($P(B|A)$)**: The likelihood of event B occurring *given* that event A has already occurred. - Notice how your preference for indoor/outdoor activities shifts depending on whether it is raining or sunny. The probability tree visually forks to capture these dependencies.

Concept: - To find the probability of a specific sequence of events (following a path from the root to a leaf), we multiply the probabilities along the branches: $P(A \cap B) = P(A) \times P(B \mid A)$. Real-World Utility: - Used in medical diagnosis tree models to calculate the probability of having a disease given a positive test result. - Used in Machine Learning (Decision Trees) and game theory to assess risks and expected payouts under uncertain future events.