Probability -- traffic lights (1. R=0.4, 2. R=0.5, 2x G=0.2)

In summary: Therefore, the probability of stopping at both lights is 0.1 or 10%. In summary, the probability of stopping at both lights is 10%, and the probability of stopping for at least one light is 80%.
  • #1
CynicusRex
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There are 2 traffic lights. Bart knows the probability of stopping at the first light is 40%, stopping at the second light is 50% and the probability of stopping at no lights is 20%.
  1. What is the probability of stopping at both lights?
  2. What is the probability of stopping for at least one light?
My attempt:
yu868Zl.jpg


Apparently the chance is 10% and not 20% of stopping at boh lights. I thought they were independent but the opposite is true. So I used the formula for dependent probability. Now I'm trying to figure out how I can find P(B=R | A=R)
 
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  • #2
But already earlier on you have a problem: case G G would be 0.6 * 0.5 and given is that it's only 0.2.

That tells you something about case G R !

The other given , 2nd light 0.5 / 0.5 on average, can then only be explained if case R G is a lot more likely than 0.4 * 0.5
 
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  • #3
They are dependent, yes.
You don't need formulas for this. Just consider all four options:
(A) stop at both
(B) stop at first but not at second
(C) stop at second but not at first
(D) both green

Those four options sum to a probability of 1, and you can set up three equations with the given numbers. That is sufficient to find all probabilities.
 
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  • #4
These are some serious cardinal mistakes I'm making. Thank you.
 
  • #5
I understand my mistakes. But I really don't see how I can use the formula. To calculate the conditional probability P(B=R | A=R) I need the probability of P(B=R ∩ A=R) but that is what I'm looking for in the first place.

Our lecturer did this: P(X={red}) = 40%, P(Y={red}) = 50% (probability of red at the second light)
P(X=Red ∩ Y=Red) = P(X=R | Y=R)
P(X=Red ∩ Y=Red) = P(X=R) + P(Y=R) - P(X=R ∪ Y=R) = 40% + 50% - 80%
P(X=Red ∩ Y=Red) = 10%

I don't see how he got to P(X=R ∪ Y=R) = 80%

m2ntrGn.jpg
 
  • #6
OK, you picked up GG = 0.2 and hence GR = 0.4.
To end up with *G = 0.5 you need RG = 0.3 - that's one way.
To end up with *R = 0.5 you need RR = 0.1 - that's an even more direct way.
*G is the chance you need to stop at light #2.

Teacher finds chance that one or both are red = 100% - chance that both are green (which is given). That explains the 80%.
But I can't follow the logic in
TheBlackAdder said:
P(X=Red ∩ Y=Red) = P(X=R) + P(Y=R) - P(X=R ∪ Y=R) = 40% + 50% - 80%
can you ?
 
  • #7
Oh I think I somewhat start to see what he did.
P(X=R) + P(Y=R) = 90% = The probability the first one is red (R) + the probability the second one is red (GR + RR)
-P(X=R ∪ Y=R) = The first light is red (R) or the second light is red (GR) or both are red (RR) ~ which equals the second question: the probability of at least one light being red = 80%

After writing this I don't see anymore. I really want to grasp this, but can't seem to find the logic. So my answer is no @BvU :(
 
  • #8
You don't need conditional probabilities at all.
If they confuse you, why do you try to keep using them?
 
  • #9
Because we need to learn to write it in a formula. I'll figure it out tomorrow. Will update this thread.
 
  • #10
Then I suggest to start with the approach I posted and to calculate conditional probabilities afterwards (unnecessary, but...).
 
  • #11
TheBlackAdder said:
Oh I think I somewhat start to see what he did.
P(X=R) + P(Y=R) = 90% = The probability the first one is red (R) + the probability the second one is red (GR + RR)
-P(X=R ∪ Y=R) = The first light is red (R) or the second light is red (GR) or both are red (RR) ~ which equals the second question: the probability of at least one light being red = 80%

After writing this I don't see anymore. I really want to grasp this, but can't seem to find the logic. So my answer is no @BvU :(

Let R1 = {first is red (stop)}, R2 = {second is red (stop)}. You are given ##P(R_1) = 0.4, P(R_2) = 0.5## and ##P(\text{not}(R_1 \cup R_2)) = 0.2##. Thus, ##P(R_1 \cup R_2) = 1-0.2 = 0.8##. The inclusion-exclusion principle says that
[tex]P(R_1 \cup R_2) = P(R_1) + P(R_2) - P(R_1 \cap R_2), [/tex]
so ##P(R_1 \cap R_2) = 0.4 + 0.5 - 0.8 = 0.1##.
 
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1. What does R=0.4 mean in the context of traffic lights?

R=0.4 means that there is a 40% chance that the traffic light will be red at any given time. This is also known as the probability of the red light being on.

2. How does R=0.5 differ from R=0.4 in terms of traffic lights?

R=0.5 means that there is a 50% chance that the traffic light will be red at any given time. This is a higher probability compared to R=0.4, which means that the red light will be on more frequently.

3. What does it mean when there are two green lights with a probability of 0.2 each?

This means that there is a 20% chance that both green lights will be on at the same time. This could occur if the traffic light has two separate green lights for different directions, and both have a probability of 0.2.

4. How do these probabilities affect the overall flow of traffic?

The probabilities of the traffic lights determine how often each color will be displayed. For example, a higher probability for the red light (R=0.5) would result in longer wait times at the traffic light, causing a slower flow of traffic. On the other hand, a lower probability for the red light (R=0.4) would result in shorter wait times and a faster flow of traffic.

5. Can the probabilities of the traffic lights be changed?

Yes, the probabilities of the traffic lights can be changed by adjusting the timing of the lights. Traffic engineers use mathematical models to determine the most efficient timing for traffic lights in order to optimize traffic flow.

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