Let the random variable X have the probability distribution listed in the table below. Determine the probability distributions of the random variable (X+1)². k 2 3 4 5 6 Pr(X=k) 0.2 0.2 0.2 0.3 0.1 Fill in the table for the probability distribution of the variable (X+1)². Pr((x + 1)² = k) k 9 16 25 36 49
Let the random variable X have the probability distribution listed in the table below. Determine the probability distributions of the random variable (X+1)². k 2 3 4 5 6 Pr(X=k) 0.2 0.2 0.2 0.3 0.1 Fill in the table for the probability distribution of the variable (X+1)². Pr((x + 1)² = k) k 9 16 25 36 49
A First Course in Probability (10th Edition)
10th Edition
ISBN:9780134753119
Author:Sheldon Ross
Publisher:Sheldon Ross
Chapter1: Combinatorial Analysis
Section: Chapter Questions
Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...
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
Transcribed Image Text:**Title: Understanding Probability Distribution Transformation**
**Objective:**
Learn how to determine the probability distribution of a transformed random variable.
**Problem Statement:**
Let the random variable \( X \) have the probability distribution listed in the table below. Determine the probability distribution of the random variable \((X + 1)^2\).
**Given Probability Distribution:**
| \( k \) | \( \Pr(X = k) \) |
|---------|-----------------|
| 2 | 0.2 |
| 3 | 0.2 |
| 4 | 0.2 |
| 5 | 0.3 |
| 6 | 0.1 |
**Task:**
Fill in the table for the probability distribution of the variable \((X + 1)^2\).
**Transformations:**
- When \( X = 2 \), \((X + 1)^2 = 3^2 = 9\).
- When \( X = 3 \), \((X + 1)^2 = 4^2 = 16\).
- When \( X = 4 \), \((X + 1)^2 = 5^2 = 25\).
- When \( X = 5 \), \((X + 1)^2 = 6^2 = 36\).
- When \( X = 6 \), \((X + 1)^2 = 7^2 = 49\).
**Table for \((X + 1)^2\):**
| \( k \) | \( \Pr((X + 1)^2 = k) \) |
|---------|-------------------------|
| 9 | |
| 16 | |
| 25 | |
| 36 | |
| 49 | |
**Instructions:**
Calculate the probabilities for each transformed value and fill the table. The probability for each value is the sum of probabilities that map to it based on the transformation.
**Example Calculation for Clarity:**
Determine \(\Pr((X + 1)^2 = 9)\):
- Based on transformation, \(\Pr(X = 2)\) fully contributes to \(\Pr((X + 1)^2 = 9)\).
- Therefore, \(\Pr((X + 1)^2 = 9) =
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