Math Problem Statement

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Part 1

At one liberal arts​ college, students are classified as humanities​ majors, science​ majors, or undecided. The chances are

4040​%

that a humanities major will change to a science major from one year to the​ next, and

2525​%

that a humanities major will change to undecided. A science major will change to humanities with probability

0.350.35​,

and to undecided with probability

0.450.45.

An undecided will switch to humanities or science with probabilities of

0.300.30

and

0.400.40​,

respectively. Complete parts ​(a) and​ (b) below.

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Part 1

​(a)**** Find the​ long-range prediction for the fraction of students in each of these three majors.

​First, find the transition matrix P. Let the first state be that a student is a humanities​ major, the second that a student is a science​ major, and the third state that a student is undecided.

Pequals=Start 3 By 3 Table 1st Row 1st Column 0.35 2nd Column 0.40 3rd Column 0.25 2nd Row 1st Column 0.35 2nd Column 0.20 3rd Column 0.45 3rd Row 1st Column 0.30 2nd Column 0.40 3rd Column 0.30 EndTable

0.35

0.40

0.25

0.35

0.20

0.45

0.30

0.40

0.30

​(Type an integer or decimal for each matrix​ element.)

Part 2

Find the​ long-range prediction for the fraction of students in each of these three majors.

The​ long-range prediction is

one third13

​humanities,

one third13

​science, and

one third13

undecided.

​(Type integers or simplified​ fractions.)

Part 3

​(b)**** For a regular​ 2-by-2 matrix having column sums of​ 1, the equilibrium vector is

Start 1 By 2 Table 1st Row 1st Column one half 2nd Column one half EndTable

12

12

.

Make a​ conjecture, and describe how this​ conjecture, if​ true, would allow you to predict the answer to part​ (a) with very little computation.

A regular​ 3-by-3 matrix having column sums of 1 has an equilibrium vector of

enter your response here.

​(Type an integer or simplified fraction for each matrix​ element.)

Solution

Part 1(a): Transition Matrix PP

The problem describes the transitions between states (humanities, science, and undecided) as follows:

  • Humanities:

    • Stays humanities: 10.400.25=0.351 - 0.40 - 0.25 = 0.35
    • Changes to science: 0.400.40
    • Changes to undecided: 0.250.25
  • Science:

    • Changes to humanities: 0.350.35
    • Stays science: 10.350.45=0.201 - 0.35 - 0.45 = 0.20
    • Changes to undecided: 0.450.45
  • Undecided:

    • Changes to humanities: 0.300.30
    • Changes to science: 0.400.40
    • Stays undecided: 10.300.40=0.301 - 0.30 - 0.40 = 0.30

The transition matrix PP is:

0.35 & 0.40 & 0.25 \\ 0.35 & 0.20 & 0.45 \\ 0.30 & 0.40 & 0.30 \end{bmatrix}$$ --- ### **Part 1(b): Long-range Prediction (Stationary Distribution)** To find the long-range prediction, solve for the stationary distribution $$\pi = [\pi_1, \pi_2, \pi_3]$$, such that $$\pi P = \pi$$ and $$\pi_1 + \pi_2 + \pi_3 = 1$$. From computations, the stationary distribution is: $$\pi = \left[\frac{1}{3}, \frac{1}{3}, \frac{1}{3}\right]$$ This means the **long-range prediction** is: - Humanities: $$\frac{1}{3}$$ (approximately 33.33%) - Science: $$\frac{1}{3}$$ (approximately 33.33%) - Undecided: $$\frac{1}{3}$$ (approximately 33.33%) --- ### **Part 1(c): Conjecture for a Regular 3x3 Matrix** For a **regular** $$3 \times 3$$ transition matrix where all column sums equal 1, the equilibrium vector (stationary distribution) has **equal components** if: 1. The system is symmetric in transitions, meaning no bias exists favoring one state over another. 2. All states are reachable, and the transitions stabilize over time. #### Conjecture: If $$P$$ is a **regular $$3 \times 3$$** matrix with column sums of 1, the equilibrium vector is: $$\pi = \left[\frac{1}{3}, \frac{1}{3}, \frac{1}{3}\right]$$ This conjecture applies due to the symmetry of the system, and it predicts the answer to **part (a)** with little computation. Specifically, each state will eventually hold an equal fraction of the population. --- ### Final Answers: - Transition matrix $$P$$: $$P = \begin{bmatrix} 0.35 & 0.40 & 0.25 \\ 0.35 & 0.20 & 0.45 \\ 0.30 & 0.40 & 0.30 \end{bmatrix}$$ - Long-range prediction (stationary distribution): $$\left[\frac{1}{3}, \frac{1}{3}, \frac{1}{3}\right]$$ - Conjecture for a regular $$3 \times 3$$ matrix: Stationary distribution is $$\left[\frac{1}{3}, \frac{1}{3}, \frac{1}{3}\right]$$. --- ### Questions to Explore: 1. Why is the stationary distribution equal for this particular transition matrix? 2. What happens if one state becomes unreachable? How does the equilibrium change? 3. How can we quickly identify whether a matrix is regular without detailed calculations? 4. What is the relationship between eigenvalues and stationary distributions in Markov processes? 5. How do the transition probabilities affect the speed of convergence to equilibrium? ### Tip: For a regular $$n \times n$$ Markov matrix where all states are symmetric and reachable, the stationary distribution is $$\frac{1}{n}$$ for each state. Always check for symmetry and regularity when analyzing such problems!

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Math Problem Analysis

Mathematical Concepts

Probability
Markov Chains
Stationary Distribution
Transition Matrices

Formulas

Transition Matrix: Rows represent the probability of moving between states.
Stationary Distribution: πP = π and π₁ + π₂ + ... + πₙ = 1

Theorems

Markov Chain Convergence Theorem

Suitable Grade Level

Grades 10-12, College-level introductory math