Let x be a Poisson random variable with μ = 4.5. Find the probabilities for x using Table 2. (Round your answers to three decimal places.) P(x ≤ 3) 0.342 P(x > 3) P(x = 3) X P(3 ≤ x ≤ 5)
Let x be a Poisson random variable with μ = 4.5. Find the probabilities for x using Table 2. (Round your answers to three decimal places.) P(x ≤ 3) 0.342 P(x > 3) P(x = 3) X P(3 ≤ x ≤ 5)
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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![**Problem Statement:**
Let \( x \) be a Poisson random variable with \( \mu = 4.5 \). Find the probabilities for \( x \) using Table 2. (Round your answers to three decimal places.)
**Probability Calculations:**
1. **\( P(x \leq 3) \)**
Entered Value: **0.342** ✅
2. **\( P(x > 3) \)**
Value not provided.
3. **\( P(x = 3) \)**
Entered Value: Incorrect ❌
4. **\( P(3 \leq x \leq 5) \)**
Value not provided.
**Instructions:**
Ensure all probabilities are calculated using the relevant Poisson distribution table and round your answers to three decimal places.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fc303f822-5e20-4d30-8920-178170554c96%2F4d980c8d-4901-4353-a4da-2487dc03a181%2F7ofc89c_processed.png&w=3840&q=75)
Transcribed Image Text:**Problem Statement:**
Let \( x \) be a Poisson random variable with \( \mu = 4.5 \). Find the probabilities for \( x \) using Table 2. (Round your answers to three decimal places.)
**Probability Calculations:**
1. **\( P(x \leq 3) \)**
Entered Value: **0.342** ✅
2. **\( P(x > 3) \)**
Value not provided.
3. **\( P(x = 3) \)**
Entered Value: Incorrect ❌
4. **\( P(3 \leq x \leq 5) \)**
Value not provided.
**Instructions:**
Ensure all probabilities are calculated using the relevant Poisson distribution table and round your answers to three decimal places.
![### Table 2: Cumulative Poisson Probabilities
This table provides cumulative Poisson probabilities, presenting values as \( P(X \leq k) = p(0) + p(1) + \cdots + p(k) \). The computations are rounded to the third decimal place. The table is structured with various values of \( \mu \), representing the mean number of events in a fixed interval, across the top and values of \( k \), representing the number of events, along the side.
#### Table Breakdown:
1. **Columns and Rows:**
- The top row signifies \( \mu \) values ranging from 0.1 to 7.0.
- The left column indicates the \( k \) values from 0 to 17.
2. **Values in the Table:**
- Each cell contains the probability that the number of events \( X \) is less than or equal to \( k \) given a particular \( \mu \).
3. **First Portion of the Table (Top):**
- Deals with smaller \( \mu \) values: 0.1 to 1.5 and \( k \) values from 0 to 7.
- Illustrates probabilities decreasing as \( \mu \) lowers and/or \( k \) increases.
4. **Second Portion of the Table (Bottom):**
- Covers larger \( \mu \) values: 2.0 to 7.0 and \( k \) values from 0 to 17.
- Shows probabilities decreasing gradually as \( k \) increases, especially pronounced in higher \( \mu \) values.
5. **Observation:**
- Cumulative probabilities approach 1.000 as \( k \) increases, indicating the likelihood of observing up to \( k \) events becomes more certain with increased \( k \) or \( \mu \).
This table is useful for statistical calculations involving Poisson processes, ideal for understanding the probability distribution of events happening independently within a fixed interval.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fc303f822-5e20-4d30-8920-178170554c96%2F4d980c8d-4901-4353-a4da-2487dc03a181%2Fvs3o6sa_processed.png&w=3840&q=75)
Transcribed Image Text:### Table 2: Cumulative Poisson Probabilities
This table provides cumulative Poisson probabilities, presenting values as \( P(X \leq k) = p(0) + p(1) + \cdots + p(k) \). The computations are rounded to the third decimal place. The table is structured with various values of \( \mu \), representing the mean number of events in a fixed interval, across the top and values of \( k \), representing the number of events, along the side.
#### Table Breakdown:
1. **Columns and Rows:**
- The top row signifies \( \mu \) values ranging from 0.1 to 7.0.
- The left column indicates the \( k \) values from 0 to 17.
2. **Values in the Table:**
- Each cell contains the probability that the number of events \( X \) is less than or equal to \( k \) given a particular \( \mu \).
3. **First Portion of the Table (Top):**
- Deals with smaller \( \mu \) values: 0.1 to 1.5 and \( k \) values from 0 to 7.
- Illustrates probabilities decreasing as \( \mu \) lowers and/or \( k \) increases.
4. **Second Portion of the Table (Bottom):**
- Covers larger \( \mu \) values: 2.0 to 7.0 and \( k \) values from 0 to 17.
- Shows probabilities decreasing gradually as \( k \) increases, especially pronounced in higher \( \mu \) values.
5. **Observation:**
- Cumulative probabilities approach 1.000 as \( k \) increases, indicating the likelihood of observing up to \( k \) events becomes more certain with increased \( k \) or \( \mu \).
This table is useful for statistical calculations involving Poisson processes, ideal for understanding the probability distribution of events happening independently within a fixed interval.
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