Theoretical Probabilities 1. What is the theoretical probability of an unfavorable outcome? \( P(x \neq 1)= \) 1 \( ( \) fraction \( )= \) \( 1 / 3 \) \( \times \) \% (Round to the nearest percent.) 2. In the questions above, which is an exact answer? The fraction Which is the approximate answer? The percentage (NOTE: The percentages above are approximations because they were non-terminating and we had to round. Some percentages are exact answers. For example, \( \frac{1}{5}=0.20=20 \% \) ) 3. How do the fractions of the total outcomes and theoretical probability compare? The fractions of the total outcomes is the same as the theoretical probability \( \uparrow \) 4. What is the sum of the probabithies of the favorable outcomes and the unfavorable outcomes, \( P(x=1)+P(x \neq 1) \) ? \( \square \) 2 What is the percentage? \( \square \) 100 \%
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Did you know that the concept of probability dates back to the 16th century, when it was primarily studied by gamblers? Mathematicians like Gerolamo Cardano and Blaise Pascal were among the first to formally document how to calculate odds, paving the way for today’s probability theory. This historical origin highlights just how long people have been fascinated by chance, seeking to understand and predict outcomes in uncertain environments. In real-world applications, theoretical probability is not just confined to games of chance. It’s used in various fields like finance, insurance, and even artificial intelligence! For instance, in finance, analysts use probability to assess the risk of investments, while in AI, algorithms can make decisions based on the likelihood of various outcomes based on historical data. Understanding theoretical probabilities can help in making informed decisions, whether it’s rolling dice or investing your money!