Question

If someone's gossip vector is vec(x)=[[1],[0]] then this means they believe that there will be an election called. If someone's gossip vector is vec(x)=[[0],[1]] then this means they believe that there won't be an election called. If someone's gossip vector is vec(x)=[[0.2],[0.8]], there's a 20% chance they believe there will be an election called and there's an 80% chance they believe there won't be an election called. How will we model gossiping? First, we'll assume that when a person gossips with another, they'll spread their own belief correctly with a probability p=0.555. This means they'll spread their own belief incorrectly with probability 0.445. You want to set up a transition matrix P=[[p_(11),p_(12)],[p_(21),p_(22)]] Assume someone in the PMO (Prime Minister's Office) knows there WILL be an election. Their gossip vector is vec(x)_(PMO). If they gossip with a neighbour, then the neighbour's gossip vector will be Pvec(x)_(PMO). If the neighbour's gossip vector equals Pvec(x)_(PMO) then this gives you some information about the entries of P. On the other hand, assume someone in the PMO (Prime Minister's Office) knows there WON'T be an election. Then their gossip vector will be vec(x)_(PMO)=[]. If they gossip with a neighbour about the election, then the neighbour's gossip vector will be []. If the neighbour's gossip vector equals Pvec(x)_(PMO) then this gives you some information about the entries of P. The transition matrix is Do you know if there a steady-state vector for this Markov chain? If so, what is the steady-state vector? minister decides one day that there WILL be an election. They tell their staff and their staff tell their neighbours and the r tell their friends and so on and so on. The 100th person in this chain has a gossip vector of about prime minister decides one day that there WON'T be an election. They tell their staff and their staff tell their neighbours and neighbours tell their friends and so on and so on. The 100th person in this chain has a gossip vector of about ion: Do you think this is a reasonable model of gossip? Why/why not? Discuss with a classmate; you are not required to subr discussion. Select a blank to input an answer If someone's gossip vector is then this means they believe that there will be an election called. If someone's gossip vector is then this means they believe that there won't be an election called. If someone's gossip vector is believe there won't be an election called. How will we model gossiping? First, we'll assume that when a person gossips with another, they'll spread their own belief correctly with a probability p = 0.555. This means they'll spread their own belief incorrectly with probability 0.445. You want to set up a transition matrix P=[[p_(11),p_(12)],[p_(21),p_(22)]] Assume someone in the PMO (Prime Minister's Office) knows there WILL be an election. Their gossip vector is vec(x)_(PMO). If they gossip with a neighbour, then the neighbour's gossip vector will be If the neighbour's gossip vector equals Pvec(x)_(PMO) then this gives you some information about the entries of P. On the other hand, assume someone in the PMO (Prime Minister's Office) knows there WON'T be an election. Then their gossip vector will be vec(x)_(PMO). If they gossip with a neighbour about the election, then the neighbour's gossip vector will be If the neighbour's gossip vector equals Pvec(x)_(PMO) then this gives you some information about the entries of P. The transition matrix is Do you know if there a steady-state vector for this Markov chain? If so, what is the steady-state vector? minister decides one day that there WILL be an election. They tell their staff and their staff tell their neighbours and the r tell their friends and so on and so on. The 100th person in this chain has a gossip vector of about prime minister decides one day that there WON'T be an election. They tell their staff and their staff tell their neighbours and neighbours tell their friends and so on and so on. The 100th person in this chain has a gossip vector of about ion: Do you think this is a reasonable model of gossip? Why/why not? Discuss with a classmate: you are not required to subr discussion. Select a blank to input an answer

Name: if someones gossip vector is vecx10 then this means they believe that there will be an election called if someones gossip vector is vecx01 then this means they believe that there wont be an 30895
Uploaded: 2023-11-14T18:30:07-08:00
Duration: 1 min 40 s
Channel: Akash M
Description: if someones gossip vector is vecx10 then this means they believe that there will be an election called if someones gossip vector is vecx01 then this means they believe that there wont be an 30895

          If someone's gossip vector is vec(x)=[[1],[0]] then this means they believe that there will be an election called.
If someone's gossip vector is vec(x)=[[0],[1]] then this means they believe that there won't be an election called.
If someone's gossip vector is vec(x)=[[0.2],[0.8]], there's a 20% chance they believe there will be an election called and there's an 80% chance they believe there won't be an election called.
How will we model gossiping? First, we'll assume that when a person gossips with another, they'll spread their own belief correctly with a probability p=0.555. This means they'll spread their own belief incorrectly with probability 0.445.
You want to set up a transition matrix
P=[[p_(11),p_(12)],[p_(21),p_(22)]]
Assume someone in the PMO (Prime Minister's Office) knows there WILL be an election. Their gossip vector is vec(x)_(PMO). If they gossip with a neighbour, then the neighbour's gossip vector will be Pvec(x)_(PMO). If the neighbour's gossip vector equals Pvec(x)_(PMO) then this gives you some information about the entries of P.
On the other hand, assume someone in the PMO (Prime Minister's Office) knows there WON'T be an election. Then their gossip vector will be vec(x)_(PMO)=[]. If they gossip with a neighbour about the election, then the neighbour's gossip vector will be []. If the neighbour's gossip vector equals Pvec(x)_(PMO) then this gives you some information about the entries of P.
The transition matrix is
Do you know if there a steady-state vector for this Markov chain?
If so, what is the steady-state vector?
minister decides one day that there WILL be an election. They tell their staff and their staff tell their neighbours and the r tell their friends and so on and so on. The 100th person in this chain has a gossip vector of about prime minister decides one day that there WON'T be an election. They tell their staff and their staff tell their neighbours and neighbours tell their friends and so on and so on. The 100th person in this chain has a gossip vector of about
ion: Do you think this is a reasonable model of gossip? Why/why not? Discuss with a classmate; you are not required to subr discussion.
Select a blank to input an answer
If someone's gossip vector is
then this means they believe that there will be an election called.
If someone's gossip vector is
then this means they believe that there won't be an election called.
If someone's gossip vector is
believe there won't be an election called.
How will we model gossiping? First, we'll assume that when a person gossips with another, they'll spread their own belief correctly with a probability p = 0.555. This means they'll spread their own belief incorrectly with probability 0.445.
You want to set up a transition matrix
P=[[p_(11),p_(12)],[p_(21),p_(22)]]
Assume someone in the PMO (Prime Minister's Office) knows there WILL be an election. Their gossip vector is vec(x)_(PMO).
If they gossip with a neighbour, then the neighbour's gossip vector will be
If the neighbour's gossip vector equals Pvec(x)_(PMO) then this gives you some information about the entries of P.
On the other hand, assume someone in the PMO (Prime Minister's Office) knows there WON'T be an election. Then their gossip vector will be vec(x)_(PMO).
If they gossip with a neighbour about the election, then the neighbour's gossip vector will be
If the neighbour's gossip vector equals Pvec(x)_(PMO) then this gives you some information about the entries of P.
The transition matrix is
Do you know if there a steady-state vector for this Markov chain?
If so, what is the steady-state vector?
minister decides one day that there WILL be an election. They tell their staff and their staff tell their neighbours and the r
tell their friends and so on and so on. The 100th person in this chain has a gossip vector of about
prime minister decides one day that there WON'T be an election. They tell their staff and their staff tell their neighbours and neighbours tell their friends and so on and so on. The 100th person in this chain has a gossip vector of about
ion: Do you think this is a reasonable model of gossip? Why/why not? Discuss with a classmate: you are not required to subr discussion.
Select a blank to input an answer

if someones gossip vector is vecx10 then this means they believe that there will be an election called if someones gossip vector is vecx01 then this means they believe that there wont be an 30895

Added by Alison W.

Elementary Statistics a Step by Step Approach

Allan G. Bluman 9th Edition

Instant Answer

Solved by Expert Akash M

11/14/2023

Step 1

This matrix represents the probabilities of someone changing their belief when gossiping with another person. The entries of P will depend on the probability p=0.555 of spreading their own belief correctly. Show more…

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If someone's gossip vector is vec(x)=[[1],[0]] then this means they believe that there will be an election called. If someone's gossip vector is vec(x)=[[0],[1]] then this means they believe that there won't be an election called. If someone's gossip vector is vec(x)=[[0.2],[0.8]], there's a 20% chance they believe there will be an election called and there's an 80% chance they believe there won't be an election called. How will we model gossiping? First, we'll assume that when a person gossips with another, they'll spread their own belief correctly with a probability p=0.555. This means they'll spread their own belief incorrectly with probability 0.445. You want to set up a transition matrix P=[[p_(11),p_(12)],[p_(21),p_(22)]] Assume someone in the PMO (Prime Minister's Office) knows there WILL be an election. Their gossip vector is vec(x)_(PMO). If they gossip with a neighbour, then the neighbour's gossip vector will be Pvec(x)_(PMO). If the neighbour's gossip vector equals Pvec(x)_(PMO) then this gives you some information about the entries of P. On the other hand, assume someone in the PMO (Prime Minister's Office) knows there WON'T be an election. Then their gossip vector will be vec(x)_(PMO)=[]. If they gossip with a neighbour about the election, then the neighbour's gossip vector will be []. If the neighbour's gossip vector equals Pvec(x)_(PMO) then this gives you some information about the entries of P. The transition matrix is Do you know if there a steady-state vector for this Markov chain? If so, what is the steady-state vector? minister decides one day that there WILL be an election. They tell their staff and their staff tell their neighbours and the r tell their friends and so on and so on. The 100th person in this chain has a gossip vector of about prime minister decides one day that there WON'T be an election. They tell their staff and their staff tell their neighbours and neighbours tell their friends and so on and so on. The 100th person in this chain has a gossip vector of about ion: Do you think this is a reasonable model of gossip? Why/why not? Discuss with a classmate; you are not required to subr discussion. Select a blank to input an answer If someone's gossip vector is then this means they believe that there will be an election called. If someone's gossip vector is then this means they believe that there won't be an election called. If someone's gossip vector is believe there won't be an election called. How will we model gossiping? First, we'll assume that when a person gossips with another, they'll spread their own belief correctly with a probability p = 0.555. This means they'll spread their own belief incorrectly with probability 0.445. You want to set up a transition matrix P=[[p_(11),p_(12)],[p_(21),p_(22)]] Assume someone in the PMO (Prime Minister's Office) knows there WILL be an election. Their gossip vector is vec(x)_(PMO). If they gossip with a neighbour, then the neighbour's gossip vector will be If the neighbour's gossip vector equals Pvec(x)_(PMO) then this gives you some information about the entries of P. On the other hand, assume someone in the PMO (Prime Minister's Office) knows there WON'T be an election. Then their gossip vector will be vec(x)_(PMO). If they gossip with a neighbour about the election, then the neighbour's gossip vector will be If the neighbour's gossip vector equals Pvec(x)_(PMO) then this gives you some information about the entries of P. The transition matrix is Do you know if there a steady-state vector for this Markov chain? If so, what is the steady-state vector? minister decides one day that there WILL be an election. They tell their staff and their staff tell their neighbours and the r tell their friends and so on and so on. The 100th person in this chain has a gossip vector of about prime minister decides one day that there WON'T be an election. They tell their staff and their staff tell their neighbours and neighbours tell their friends and so on and so on. The 100th person in this chain has a gossip vector of about ion: Do you think this is a reasonable model of gossip? Why/why not? Discuss with a classmate: you are not required to subr discussion. Select a blank to input an answer