Q3:What are the probabilities of correctly identifying thornbill species?

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In summary, part 1 of the conversation shows that if Harry sees a thornbill, the probability that he thinks it is a yellow-rumped is .6.ii) If a user is a Bronze member at the beginning of April, the probability that they will be a Gold member at the beginning of June is 0.90.
  • #1
sam_0017
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hi can anyone help my whit this questions :confused:

Q1:

Harry is an amateur birdwatcher who goes birdwatching in a region in which he knows there are only two species of thornbill – the buff-rumped thornbill and the yellow-rumped thornbill. Harry has some difficulty in differentiating the two species (but he does know a thornbill when he sees one). If Harry sees a buff-rumped thornbill, he will correctly identify it 80% of the time. If he sees a yellow-rumped thornbill, he will correctly identify it 60% of the time. In this region, 70% of the thornbills are buff-rumped.

(i) If Harry sees a thornbill, what is the probability that he thinks it is a yellow-rumped?

Harry goes birdwatching in this region with George who is a thornbill expert. If Harry correctly identifies a thornbill, George will correctly identify it 99% of the time. If Harry misidentifies a thornbill, George will correctly identify it 90% of the time.

(ii) Harry and George both spot a thornbill which they both identify as a yellow-rumped. What is the probability that the bird is in fact buff-rumped?

=============================================

Q2:

At the start of each month, Microsoft classifies Xbox Live users either as Gold, Silver or Bronze members. Gold members have a 70% chance of staying a Gold member, and can never become Bronze members by the end of the next month. If a user is a Silver member at the start of a given month, then they are 3 times as likely as becoming a Gold member compared with a Bronze member at the start of the next month. They also have a 40% chance of staying a Silver member.
Finally, 50% of Bronze members remain Bronze members, while 50% become Silver members at the start of the next month. For the 50% of Bronze members who would become Silver members at the start of the next month, Microsoft randomly offers 10% of these users a chance to become a Gold member at the start of the next months (hence it is possible for Bronze members to become Gold members in one month). To accept this offer, the user must pay a small fee, so not everybody accepts. Microsoft estimates that 90% of Bronze members accept this offer.

(a) Set up the probability transition matrix for this Markov chain, with a user’s membership considered at the beginning of each month.

(b) If a user is a Bronze member at the beginning of April, what is the probability that they will be a Gold member at the beginning of June?

(c) Determine the proportion of users who are Gold members in the long run.
 
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  • #2


It might be useful to draw a tree of possibilities:
Code:
         /\
        /  \
   yellow   not yellow
     /\          /\
    /  \        /  \
   /    \    right wrong
 right wrong

Now add the given probabilities. Which path(s) through the tree identifyies(y) the situation in (i)?
 
  • #3


what about Q1 (II) and Q2
 
  • #4


You're welcome.

Did you manage to do Q1 (I), because (II) is quite similar.

Please be a little more specific in your question, we're not going to do your problems for you.
Q2 is a really straightforward question about Markov chains (it's like they filled out "the" template for Markov chain problem sets :-)), so what are you having trouble with?
 
  • #5


hi,

Q1:

Part 1:

P(buff-rumped) = .7
P(yellow-rumped) = .3

P(Harry correctly identifies buff-rumped)=.8
P(Harry incorrectly identifies buff-rumped)=.2


P(Harry correctly identifies yellow-rumped)=.6
P(Harry incorrectly identifies yellow-rumped)=.4

P(Harry thinks it is a yelow-rumped)=.18

hope this helps. If you truly understand this; you will do 2nd part without any difficulty, if not find a different subject that you will enjoy while you're learning!
 
  • #6


Thanks,
but i solve the problem this way and i don't know is it correct or not:

i.
p(yellow, harry thinks it's yellow) = 0.3 * 0.6 = 0.18
p(yellow, harry thinks it's buff) = 0.3 * 0.4 = 0.12
p(buff, harry thinks it's yellow) = 0.7 * 0.2 = 0.14
p(buff, harry thinks it's buff) = 0.7 * 0.8 = 0.56
=> p(harry think it's yellow) = 0.18 + 0.14 = 0.32

ii. There are two ways they can both say yellow:
p(yellow, harry thinks yellow, george correctly agrees) = 0.18 * 0.99 = 0.1782
p(buff, harry thinks yellow, george incorrectly agrees) = 0.14 * 0.10 = 0.014
=> p(actually buff) = 0.014 / (0.014 + 0.1782)
 
  • #7


Your answer for i) looks good.
For ii), why do you divide by (0.014 + 0.1782)? Isn't 0.014 already the answer?
 
  • #8


you can see P ( A|B) = p(A [itex]\cap[/itex] B) /p (B)
 

What is a tree of possibilities?

A tree of possibilities is a visual representation used in decision analysis and game theory to map out all possible outcomes of a decision or situation. It consists of a series of branches, with each branch representing a possible choice or action and the subsequent branches representing the possible outcomes of that choice.

How is a tree of possibilities useful in scientific research?

A tree of possibilities can be useful in scientific research as it helps scientists to systematically organize and analyze all possible outcomes of a particular experiment or study. It allows for a more comprehensive understanding of the potential results and can aid in the decision-making process for future experiments.

Can a tree of possibilities be used for any type of research?

Yes, a tree of possibilities can be used for any type of research as it is a general method for organizing and analyzing all possible outcomes. It can be applied to various fields such as biology, physics, psychology, and more.

How do you create a tree of possibilities?

To create a tree of possibilities, you start with a central node representing the initial decision or situation. From there, you branch out into all possible choices or actions, with each subsequent branch representing the possible outcomes of that choice. This process continues until all possible outcomes have been mapped out.

What are the benefits of using a tree of possibilities?

Using a tree of possibilities can help to identify the most favorable outcomes and assess the potential risks and uncertainties of a decision. It also allows for a clearer visualization of all possible outcomes, making it easier to make informed decisions and plan for the future.

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