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Reil
19 days ago
11

Radio blackouts are among the most common space weather events to affect Earth. Minor radio blackouts occur, on average, twice p

er year. Use a Poisson process to model the phenomenon. (a) Given that 3 events have occurred in the first half of the year, what is that probability that 3 events will happen in the rest of the year? (b) How many radio blackouts do you expect to see in two years? (c) Starting from now, how long must we wait so that the probability of seeing the next radio blackout is at least 0.5? (d) Find the probability that the time to the 4th blackout is at most 2 years.
Mathematics
1 answer:
Zina [9.1K]19 days ago
8 0

Answer:

a.  P(x = 3) = 0.061313

b. The anticipated number of radio blackouts = 4

c.  It's unclear when the next radio blackout will occur.

d. P(x = 4) = 0.19537

Step-by-step explanation:

Based on the provided details:

A Poisson process is utilized to model the occurrence of this event:

Minor radio blackouts occur, on average, two times annually.

Therefore:

\lambda = 2 \ years

For question (a)

time t = 1/2 (i.e., six months)

Let x represent the likelihood of 3 incidents during the remaining months of the year.

Then:

P(x = 3) = \dfrac{e^{-\lambda t} \times (\lambda t)^x}{x!}

P(x = 3) = \dfrac{e^{-2* 0.5} \times (2 * 0.5)^3}{3!}

P(x = 3) = 0.061313

b).

The expected number of radio blackouts over two years is calculated as follows:

We start with:

t = 2 years

E(x) = λ × t

E(x) = 2 × 2

E(x) = 4

Thus, the predicted number of radio blackouts = 4

c).

The time we must wait until the probability of witnessing the next radio blackout reaches at least 0.5 is as follows:

In this case, time (t) =???

Thus:

P(x =1) = 0.5

P(x = 1) = \dfrac{e^{-\lambda t} \times (\lambda t)^x}{x!} = 0.5

\dfrac{e^{-\lambda t} \times (\lambda t)^x}{x!} = 0.5

Consequently, we are unable to ascertain the probability (50%) of the next radio blackout.

d)

We can compute the probability that the time until the fourth blackout is at most 2 years as follows:

Here;

x =4, t = 2

Thus:

P(x = 4) = \dfrac{e^{-4 } \times (4)^4}{4!}

P(x = 4) = 0.19537

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