Westonci.ca makes finding answers easy, with a community of experts ready to provide you with the information you seek. Join our Q&A platform to connect with experts dedicated to providing precise answers to your questions in different areas. Explore comprehensive solutions to your questions from a wide range of professionals on our user-friendly platform.
Sagot :
Sure! Let's go through this step-by-step.
Step 1: Understanding the Binomial Distribution Formula
The binomial distribution formula is given by:
[tex]\[ P(r) = C(n, r) \cdot p^r \cdot (1 - p)^{n - r} \][/tex]
where:
- [tex]\( P(r) \)[/tex] is the probability of having exactly [tex]\( r \)[/tex] successes in [tex]\( n \)[/tex] trials.
- [tex]\( C(n, r) \)[/tex] is the binomial coefficient, which describes the number of ways to choose [tex]\( r \)[/tex] successes out of [tex]\( n \)[/tex] trials, and is calculated as [tex]\( \frac{n!}{r!(n-r)!} \)[/tex]
- [tex]\( p \)[/tex] is the probability of success on a single trial.
- [tex]\( (1 - p) \)[/tex] is the probability of failure on a single trial.
- [tex]\( n \)[/tex] is the total number of trials.
- [tex]\( r \)[/tex] is the number of successes we are interested in.
Step 2: Calculate the Binomial Coefficient [tex]\( C(n, r) \)[/tex]
Given [tex]\( n = 100 \)[/tex] and [tex]\( r = 2 \)[/tex], the binomial coefficient [tex]\( C(n, r) \)[/tex] is:
[tex]\[ C(100, 2) = \frac{100!}{2!(100-2)!} \][/tex]
This can be computed as:
[tex]\[ C(100, 2) = \frac{100 \times 99}{2 \times 1} = 4950 \][/tex]
Step 3: Compute the Probability [tex]\( P(r) \)[/tex]
Next, we need to plug in the values into the binomial distribution formula. Given [tex]\( p = 0.03 \)[/tex], [tex]\( n = 100 \)[/tex], and [tex]\( r = 2 \)[/tex], we get:
[tex]\[ P(2) = C(100, 2) \cdot (0.03)^2 \cdot (1 - 0.03)^{100 - 2} \][/tex]
[tex]\[ P(2) = 4950 \cdot (0.03)^2 \cdot (0.97)^{98} \][/tex]
Let's break it down:
1. Compute [tex]\( (0.03)^2 = 0.0009 \)[/tex]
2. Compute [tex]\( (0.97)^{98} \approx 0.0452 \)[/tex]
Now, multiply these together along with the binomial coefficient:
[tex]\[ P(2) = 4950 \cdot 0.0009 \cdot 0.0452 \approx 0.2252 \][/tex]
Step 4: Rounding the Final Answer
Finally, we round our result to four decimal places:
[tex]\[ P(2) \approx 0.2252 \][/tex]
So, for [tex]\( n = 100 \)[/tex], [tex]\( p = 0.03 \)[/tex], and [tex]\( r = 2 \)[/tex], the probability [tex]\( P(r) \)[/tex] is approximately 0.2252.
Step 1: Understanding the Binomial Distribution Formula
The binomial distribution formula is given by:
[tex]\[ P(r) = C(n, r) \cdot p^r \cdot (1 - p)^{n - r} \][/tex]
where:
- [tex]\( P(r) \)[/tex] is the probability of having exactly [tex]\( r \)[/tex] successes in [tex]\( n \)[/tex] trials.
- [tex]\( C(n, r) \)[/tex] is the binomial coefficient, which describes the number of ways to choose [tex]\( r \)[/tex] successes out of [tex]\( n \)[/tex] trials, and is calculated as [tex]\( \frac{n!}{r!(n-r)!} \)[/tex]
- [tex]\( p \)[/tex] is the probability of success on a single trial.
- [tex]\( (1 - p) \)[/tex] is the probability of failure on a single trial.
- [tex]\( n \)[/tex] is the total number of trials.
- [tex]\( r \)[/tex] is the number of successes we are interested in.
Step 2: Calculate the Binomial Coefficient [tex]\( C(n, r) \)[/tex]
Given [tex]\( n = 100 \)[/tex] and [tex]\( r = 2 \)[/tex], the binomial coefficient [tex]\( C(n, r) \)[/tex] is:
[tex]\[ C(100, 2) = \frac{100!}{2!(100-2)!} \][/tex]
This can be computed as:
[tex]\[ C(100, 2) = \frac{100 \times 99}{2 \times 1} = 4950 \][/tex]
Step 3: Compute the Probability [tex]\( P(r) \)[/tex]
Next, we need to plug in the values into the binomial distribution formula. Given [tex]\( p = 0.03 \)[/tex], [tex]\( n = 100 \)[/tex], and [tex]\( r = 2 \)[/tex], we get:
[tex]\[ P(2) = C(100, 2) \cdot (0.03)^2 \cdot (1 - 0.03)^{100 - 2} \][/tex]
[tex]\[ P(2) = 4950 \cdot (0.03)^2 \cdot (0.97)^{98} \][/tex]
Let's break it down:
1. Compute [tex]\( (0.03)^2 = 0.0009 \)[/tex]
2. Compute [tex]\( (0.97)^{98} \approx 0.0452 \)[/tex]
Now, multiply these together along with the binomial coefficient:
[tex]\[ P(2) = 4950 \cdot 0.0009 \cdot 0.0452 \approx 0.2252 \][/tex]
Step 4: Rounding the Final Answer
Finally, we round our result to four decimal places:
[tex]\[ P(2) \approx 0.2252 \][/tex]
So, for [tex]\( n = 100 \)[/tex], [tex]\( p = 0.03 \)[/tex], and [tex]\( r = 2 \)[/tex], the probability [tex]\( P(r) \)[/tex] is approximately 0.2252.
Thank you for your visit. We are dedicated to helping you find the information you need, whenever you need it. We appreciate your time. Please revisit us for more reliable answers to any questions you may have. Get the answers you need at Westonci.ca. Stay informed with our latest expert advice.