The probability that a contractor gets a plumbing contract is 2 / 3 and the probability that he will not get an electric contract is 5 / 9. If the probability of getting at least one contract is 4 / 5, then the probability that he will get both the contracts is:
14 / 45
This question asks us to calculate the probability that a contractor receives both a plumbing contract and an electric contract, given the probabilities of getting each type of contract individually and the probability of getting at least one of them.
Let's define the events:
We are given the following probabilities:
We need to find the probability that the contractor will get both contracts, which is \(P(A \cap B)\).
We are given the probability of *not* getting the electric contract, \(P(B')\). The probability of getting the electric contract, \(P(B)\), is simply 1 minus the probability of not getting it.
Using the complementary probability rule:
\( P(B) = 1 - P(B') \)
Substitute the given value:
\( P(B) = 1 - \frac{5}{9} \)
\( P(B) = \frac{9}{9} - \frac{5}{9} \)
\( P(B) = \frac{9 - 5}{9} \)
\( P(B) = \frac{4}{9} \)
So, the probability of getting the electric contract is \( \frac{4}{9} \).
The probability of getting at least one contract (plumbing or electric) is given by the formula for the union of two events:
\( P(A \cup B) = P(A) + P(B) - P(A \cap B) \)
We know \(P(A)\), \(P(B)\), and \(P(A \cup B)\). We can rearrange this formula to solve for \(P(A \cap B)\), the probability of getting both contracts:
\( P(A \cap B) = P(A) + P(B) - P(A \cup B) \)
Now, substitute the known values into the rearranged formula:
\( P(A \cap B) = \frac{2}{3} + \frac{4}{9} - \frac{4}{5} \)
To add and subtract these fractions, we need to find a common denominator. The denominators are 3, 9, and 5. The least common multiple (LCM) of 3, 9, and 5 is 45.
Convert each fraction to an equivalent fraction with a denominator of 45:
Now substitute these equivalent fractions back into the equation:
\( P(A \cap B) = \frac{30}{45} + \frac{20}{45} - \frac{36}{45} \)
Perform the addition and subtraction:
\( P(A \cap B) = \frac{30 + 20 - 36}{45} \)
\( P(A \cap B) = \frac{50 - 36}{45} \)
\( P(A \cap B) = \frac{14}{45} \)
The probability that the contractor will get both the plumbing contract and the electric contract is \( \frac{14}{45} \).
| Event | Probability |
|---|---|
| Getting Plumbing Contract (A) | \( \frac{2}{3} \) |
| Not Getting Electric Contract (B') | \( \frac{5}{9} \) |
| Getting Electric Contract (B) | \( 1 - \frac{5}{9} = \frac{4}{9} \) |
| Getting At Least One Contract (A \(\cup\) B) | \( \frac{4}{5} \) |
| Getting Both Contracts (A \(\cap\) B) | \( \frac{14}{45} \) |
Based on the calculations using the given probabilities and the formula for the probability of the union of two events, the probability that the contractor gets both the plumbing and electric contracts is \( \frac{14}{45} \).
| Concept | Explanation | Formula (for events A and B) |
|---|---|---|
| Probability of an Event | The likelihood of an event occurring. | \( P(A) = \frac{\text{Number of favorable outcomes}}{\text{Total number of possible outcomes}} \) |
| Complementary Events | Two events are complementary if one event occurs if and only if the other does not. The sum of their probabilities is 1. | \( P(A') = 1 - P(A) \) |
| Union of Events (A or B) | The event that A occurs, or B occurs, or both occur (at least one occurs). | \( P(A \cup B) = P(A) + P(B) - P(A \cap B) \) |
| Intersection of Events (A and B) | The event that both A and B occur. | \( P(A \cap B) \) (can be calculated using the union formula or conditional probability depending on the information) |
The phrase "at least one" in probability problems typically refers to the union of events. For two events, A and B, "at least one" means A happens OR B happens OR both happen. This is exactly what the union \( A \cup B \) represents.
The formula \( P(A \cup B) = P(A) + P(B) - P(A \cap B) \) is crucial here. When you simply add \(P(A)\) and \(P(B)\), you are double-counting the outcomes where both A and B occur. Therefore, you must subtract the probability of the intersection, \(P(A \cap B)\), once to correct this double-counting.
In this specific problem, we were given \(P(A \cup B)\) and asked to find \(P(A \cap B)\), which required rearranging the standard union formula. This is a common technique in probability questions.
If the data are skewed, which option of central tendency measure is the most unreliable indicator?
The Excess Kurtosis of the Geometric distribution with parameter p is:
For a distribution, the mean is 10, variance is 16, γ 1is + 1 and β 2is 4. The distribution is:
For the discrete distribution, the Pearson's coefficient of skewness β 2is always:
60% of the employees of a company are college graduates. Of these, 10% are in sales. Of the employees who did not graduate from college, 80% are in sales. The probability that an employee selected at random is in sales, is:
For a frequency distribution of a variable x, mean = 32, median = 30. The distribution is:
The first four raw moments of distribution are 2, 136, 320, and 40,000, The coefficient of skewness is:
For a distribution, the percentile partition values are P 10 = 58.983, P 50 = 61.345 and P 90 = 63.831. Kelly's coefficient of skewness is:
A box contains four soccer balls printed with numbers 112, 121, 211. 222. A footballer chooses one ball at random. Let A 1be the event that the first digit of the printed number of the ball chosen is 1. Similarly, A 2and A 3denote that second as well as third digit of the printed number is 1. The events A 1,A 2, and A 3are:
If the Bowley’s coefficient of skewness is less than zero, then the distribution is:
If the data are skewed, which option of central tendency measure is the most unreliable indicator?
Events A, Band C are mutually exclusive events such that \(P(A) = \dfrac{3x + 1}{3}, P(B) = \dfrac{1-x}{4}\)and \(P(C) = \dfrac{1-2x}{4}\)The set of possible values of x are in the interval
Let A, B be two events in a discrete probability space with ℙ(A) > 0 and ℙ(B) > 0. Which of the following are necessarily true?
The Excess Kurtosis of the Geometric distribution with parameter p is:
For a distribution, the mean is 10, variance is 16, γ 1is + 1 and β 2is 4. The distribution is: