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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 \%

Ask by Harper Hardy. in the United States
Feb 03,2025

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Tutor-Verified Answer

Answer

1. The probability of an unfavorable outcome is \( \frac{1}{3} \) or approximately \( 33\% \). 2. The exact answer is the fraction \( \frac{1}{3} \), and the approximate answer is \( 33\% \). 3. The fractions of the total outcomes and theoretical probability are the same. 4. The sum of the probabilities of favorable and unfavorable outcomes is \( 1 \) (or \( 100\% \)).

Solution

Let's break down the problem step by step. ### 1. Theoretical Probability of an Unfavorable Outcome The theoretical probability of an unfavorable outcome is given as \( P(x \neq 1) = \frac{1}{3} \). To convert this fraction into a percentage, we can use the formula: \[ \text{Percentage} = \left( \frac{\text{Fraction}}{1} \right) \times 100 \] Substituting the fraction: \[ \text{Percentage} = \left( \frac{1}{3} \right) \times 100 \] Calculating this gives: \[ \text{Percentage} = \frac{100}{3} \approx 33.33\% \] Rounding to the nearest percent, we get: \[ \text{Rounded Percentage} = 33\% \] ### 2. Exact and Approximate Answers - **Exact Answer**: The fraction \( \frac{1}{3} \) is the exact answer. - **Approximate Answer**: The percentage \( 33\% \) is the approximate answer because it was rounded. ### 3. Comparison of Fractions of Total Outcomes and Theoretical Probability The fractions of the total outcomes and the theoretical probability are indeed the same. This is because the theoretical probability is defined as the ratio of the number of favorable outcomes to the total number of outcomes. Therefore, we can conclude: \[ \text{The fractions of the total outcomes is the same as the theoretical probability} \uparrow \] ### 4. Sum of Probabilities of Favorable and Unfavorable Outcomes The sum of the probabilities of the favorable outcomes and the unfavorable outcomes is given by: \[ P(x=1) + P(x \neq 1) \] From the information provided, we know: - \( P(x \neq 1) = \frac{1}{3} \) - Since the total probability must equal 1, we can find \( P(x=1) \): \[ P(x=1) = 1 - P(x \neq 1) = 1 - \frac{1}{3} = \frac{2}{3} \] Now, summing these probabilities: \[ P(x=1) + P(x \neq 1) = \frac{2}{3} + \frac{1}{3} = 1 \] ### Percentage of the Sum of Probabilities The percentage of the sum of probabilities is: \[ \text{Percentage} = 1 \times 100 = 100\% \] ### Summary of Answers 1. \( P(x \neq 1) = \frac{1}{3} \) and rounded percentage is \( 33\% \). 2. Exact answer: The fraction \( \frac{1}{3} \); Approximate answer: The percentage \( 33\% \). 3. The fractions of the total outcomes is the same as the theoretical probability \( \uparrow \). 4. The sum of the probabilities \( P(x=1) + P(x \neq 1) = 1 \) and the percentage is \( 100\% \).

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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!

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