Interesting exercise of probability

In summary, the snake has a 65.60% chance of walking at least 10 meters before dying. This probability is calculated using a formula based on the snake's movements, where it has a 1/3 chance of turning left, right, or continuing straight at each step. This probability is obtained by calculating the chance of the snake surviving after 9 moves, which is approximately 65.60%.
  • #1
Alexsandro
51
0
A snake with a little more than 4 meters takes a walk for the forest in the following way. After to walk 1 meter in definitive direction it decides aleatoriamente if she capsizes for the left or if she capsizes for the right or if she continues in the same direction, independently of the previous decisions. However, if at some moment it finds its proper tail, it does not recognize it, bites and dies poisoned. She determines the probability of that the snake walks at least 10 meters before dying.
 
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  • #2
Consider encoding the above movements this way,
1. whenever the snake moves right, mark it as -1
2. whenever the snake moves straight, mark it as 0
3. whenever the snake moves left, mark it as 1

Thus the movements of snake can be encoded as a stream of -1's,0's and 1's.
This sequence terminates whenever we see 4 consecutive 1's or -1's.
The required probability then becomes,
P(length of sequence >=10)
= 1 - P(length of sequence<10)
I think this should be computable, albeit tedious (which is why i am avoiding doing it right now anyways).

-- AI
 
  • #3
-- and all mirror reflections state 1 whre the last 2 metres can be oriented in any way
_| " state 2 where the last 2 metres should not be oriented parallel to the first one

=| state 3

We can formulate the following:

p1(n+1)=1/3.p1(n)+1/3.p2(n)+1/3.p3(n)
p2(n+1)=2/3.p1(n)+1/3.p2(n)+1/3.p3(n)
p3(n+1)=0.p1(n)+1/3.p2(n)+0.p3(n)

which is of the form
P(n+1)=T.P(n)
So we have
P(9)=T^9.P(0)..as we need 9 movs to be alive so that it definitely moves 1 more metre
where P(0)=[1,0,0]'

SO we get

P(9)=[0.2317 0.3136 0.1108]

or pr(living)=0.6560
 
Last edited:
  • #4
To be more precise it is
12913/19683
 

1. What is probability and why is it important in science?

Probability is the measure of the likelihood of an event occurring. It is important in science because it allows us to make predictions and draw conclusions based on data and evidence. It also helps us understand and quantify uncertainty in our observations and experiments.

2. What are some common applications of probability in scientific research?

Probability is used in many areas of scientific research, including genetics, epidemiology, climate science, and psychology. It is also used in experimental design, data analysis, and modeling.

3. Can probability be used to prove or disprove a hypothesis?

No, probability cannot prove or disprove a hypothesis on its own. It is used to support or reject a hypothesis based on the likelihood of the observed data occurring under the assumptions of the hypothesis.

4. How do scientists calculate and interpret probability?

Scientists use mathematical formulas and statistical methods to calculate and interpret probability. They also consider the context and assumptions of the problem to properly interpret the probability value.

5. How does the concept of probability relate to the scientific method?

The scientific method involves making observations, forming a hypothesis, testing the hypothesis through experiments, and drawing conclusions based on the results. Probability is used to evaluate the evidence and determine the strength of the relationship between the observed data and the hypothesis, which is an essential step in the scientific method.

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