Math Problem Statement
A recent study suggested that 70% of all eligible voters will vote in the next presidential election. Suppose 20 eligible voters were randomly selected from the population of all eligible voters.
Find the probability that more than 11 of the eligible voters sampled will vote in the next presidential election.
.772
.228
.608
.113
.887
Solution
To solve this problem, we are dealing with a binomial distribution because we are considering the probability of "success" (i.e., voting) in a fixed number of trials (20 eligible voters), with a constant probability of success (70%, or ).
We are asked to find the probability that more than 11 of the 20 eligible voters sampled will vote.
Key Parameters:
- (number of trials)
- (probability of success)
- is the random variable representing the number of voters who will vote, and .
- We need , i.e., the probability that more than 11 voters vote.
From the image, the table you provided seems to contain binomial probabilities or cumulative probabilities for different values of and .
Steps:
- Look at the portion of the table for and .
- Locate the cumulative probability for , and subtract this from 1 to get .
Let's interpret the table:
- The row for and gives us a cumulative probability (at the value of 0.70).
- Using this approach, .
Calculation:
From the table provided in your image for and :
- (as found from the table for ).
Thus, the probability that more than 11 voters will vote is:
Final Answer:
The probability that more than 11 of the 20 eligible voters sampled will vote is 0.887.
Would you like more details on this solution? Here are some relative questions to explore further:
- How do you calculate probabilities for a binomial distribution manually?
- What other scenarios could use binomial distribution?
- How would the solution change if the sample size increased?
- What is the difference between cumulative probabilities and individual probabilities?
- How can we approximate binomial probabilities for large sample sizes?
Tip: Binomial distribution is often approximated by a normal distribution when the sample size is large.
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Math Problem Analysis
Mathematical Concepts
Binomial Distribution
Probability
Formulas
P(X > k) = 1 - P(X ≤ k) where X is binomially distributed
P(X = k) = (n choose k) * p^k * (1 - p)^(n-k)
Theorems
Binomial Probability Theorem
Suitable Grade Level
College-Level Statistics
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