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skad [1K]
2 years ago
15

An example problem in a Statistics textbook asked to find the probability of dying when making a skydiving jump.

Mathematics
1 answer:
MArishka [77]2 years ago
3 0

Answer:

(a) 0.999664

(b) 15052

Step-by-step explanation:

From the given data of recent years,  there were about 3,000,000 skydiving jumps and 21 of them resulted in deaths.

So, the probability of death is \frac{21}{3000000}==0.000007.

Assuming, this probability holds true for each skydiving and does not change in the present time.

So, as every skydiving is an independent event having a fixed probability of dying and there are only two possibilities, the diver will either die or survive, so, all skydiving can be regarded as is Bernoulli's trial.

Denoting the probability of dying in a single jump by q.

q=7\times 10^{-6}=0.000007.

So, the probability of survive, p=1-q

\Rightarrow p=1-7\times 10^{-6}=0.999993.

(a) The total number of jump he made, n=48

Using Bernoulli's equation, the probability of surviving in exactly 48 jumps (r=48) out of 48 jumps (n=48) is

=\binom(n,r)p^rq^{n-r}

=\binom(48,48)(0.999993)^{48}(0.000007)^{48-48}

=(0.999993)^{48}=0.999664 (approx)

So, the probability of survive in 48 skydiving is 0.999664,

(b) The given probability of surviving =90%=0.9

Let, total n skydiving jumps required to meet the surviving probability of 0.9.

So, By using Bernoulli's equation,

0.9=\binom {n }{r} p^rq^{n-r}

Here, r=n.

\Rightarrow 0.9=\binom{n}{n}p^nq^{n-n}

\Rightarrow 0.9=p^n

\Rightarrow 0.9=(0.999993)^n

\Rightarrow \ln(0.9)=n\ln(0.999993) [ taking \log_e both sides]

\Rightarrow n=\frac {\ln(0.9)}{\ln(0.999993)}

\Rightarrow n=15051.45

The number of diving cant be a fractional value, so bound it to the upper integral value.

Hence, the total number of skydiving required to meet the 90% probability of surviving is 15052.

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Given Data:

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Subtract 2/3 from your answer.

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An annexation suit against a county subdivision of 1200 residences is being considered by a neighboring city. If the occupants o
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Answer:

Probability that in a random sample of 10 at least 3 favor the annexation suit is 0.9453.

Step-by-step explanation:

We are given that an annexation suit against a county subdivision of 1200 residences is being considered by a neighboring city. The occupants of half the residences object to being annexed.

Also, a random sample of 10 residents is taken.

The above situation can be represented through Binomial distribution;

P(X=r) = \binom{n}{r}p^{r} (1-p)^{n-r} ; x = 0,1,2,3,.....

where, n = number of trials (samples) taken = 10 residents

            r = number of success = at least 3

           p = probability of success which in our question is probability that

                 residents favor the annexation suit, which is calculated as below;

p = \frac{\text{Number of residents favoring the annexation suit }}{\text{Total number of residents considered } } = \frac{600}{1200} = 0.50

<em>LET X = Number of residents favoring the annexation suit</em>

So, it means X ~ Binom(n=10, p=0.50)

Now, Probability that in a random sample of 10 at least 3 favor the annexation suit is given by = P(X \geq 3)

 P(X \geq 3)  = 1 - P(X < 3) = 1 - P(X \leq 2)

               = 1 - [P(X = 0) + P(X = 1) + P(X = 2)]

= 1- [\binom{10}{0}\times 0.50^{0} \times (1-0.50)^{10-0} + \binom{10}{1}\times 0.50^{1} \times (1-0.50)^{10-1} +\binom{10}{2}\times 0.50^{2} \times (1-0.50)^{10-2}]

= 1-[ 1 \times 1  \times 0.50^{10}+10 \times 0.50^{1}  \times 0.50^{9}+45 \times 0.50^{2}  \times 0.50^{8}]

= 1-[ 0.50^{10}+10 \times 0.50^{10}+45 \times  0.50^{10}]

= 1-0.50^{10}[ 1+10 +45 ] = 1-0.50^{10} \times 56

                                      = 0.9453

Therefore, Probability that in a random sample of 10 at least 3 favor the annexation suit is 0.9453.

8 0
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