🔢In continuous settings, probabilities cannot be assigned to individual values, but instead, we use probability density functions (PDFs) to describe the distribution.

🌡️The area under the PDF represents the probability of a range of values, solving the paradox of assigning probabilities to each individual value in an infinite set.

📚Measure theory provides a formal foundation for probability and helps unite the rules for combining probabilities in discrete and continuous settings.

⚖️Probability density functions (PDFs) allow us to calculate the probability of a range of values and answer questions about the probability of specific intervals.

🎯Probability density is better tied to possibility than probability, and different rules apply to combining probabilities of different sets in continuous settings.