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Lera25 [3.4K]
1 year ago
9

The time that a butterfly lives after emerging from its chrysalis can be modelled by a random variable tt, the model here taking

the probability that a butterfly survives for more than tt days as
Mathematics
1 answer:
4vir4ik [10]1 year ago
3 0
<span>Answer: The probabilities that either a) the butterfly dies within 7 days or b) the butterfly lives longer than 7 days must add up to one. We know the second probability (lives longer than 7 days)--it is given. So now set up an equation and solve: P(t > 7) = 36 / 13² = 36/169 --> 36/169 + x = 1 --> x = 1 - 36/169 = 133/169 ~ 0.7870 or 78.70% b) 7% is the probability (the expected value) that a butterfly will survive more than t days. Again, this formula is given: 36/(t + 6)² = 0.07 --> (t + 6)² = 36/.07 --> t = âš(36/.07) - 6 ~ 16.68 days This is the value of t that will give a probability of 7%. c) This one is a little trickier. Technically the mean lifetime should be calculated as: â«t * p(t)dt where p(t) is the probability distribution function But we have a cumulative probability distribution. I think we need to find the probability distribution from this cumulative one. Which is easy because the cumulative distribution function is an integral of the probability distribution function: P(t) = â«p(x)dx, from x = t, to x = âž Now hopefully it's easy to see that P(t) is an anti-derivative of p(x). Said the other way p(x) is the derivative of P(t): P'(t) = -72/(t + 6)Âł --> but p(t) shouldn't be negative--also you can convince yourself that it should be positive by using the above value (from t --> âž...you get -0 - a negative = a positive) p(t) = 72/(t + 6)Âł Now we can calculate the mean lifetime by integrating: 72â«t/(t + 6)Âłdt --> there's a very easy u-substitution to use here: u = t + 6 --> du = dt --> t = u - 6 --> â«(u - 6)/uÂłdu = â«(1/u² - 6/uÂł)du = -1/u + 3/u² + C --> now evaluate from t = 0 to t = âž or from u = 0 + 6 = 6 to u = âž 0 - (-1/6 + 3/36) = 1/6 - 1/12 = 1/12 --> multiply by the 72 72/12 = 6 days</span>
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If you use 8.1g of sugar for 1 cake then 6 cakes will be 48.6g of sugar

Just do 8.1*6 and you will get 48.6

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In the equation "y=m+b," what does the "m" stand for​
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The factory quality control department discovers that the conditional probability of making a manufacturing mistake in its preci
Anni [7]

Answer:

The probability that a defective ball bearing was manufactured on a Friday = 0.375

Step-by-step explanation:

Let the event of making a mistake = M

The event of making a precision ball bearing production on Monday = Mo

The event of making a precision ball bearing production on Tuesday = T

The event of making a precision ball bearing production on Wednesday = W

The event of making a precision ball bearing production on Thursday = Th

The event of making a precision ball bearing production on Friday = F

the conditional probability of making a manufacturing mistake in its precision ball bearing production is 4% on Tuesday, P(M|T) = 4% = 0.04

4% on Wednesday, P(M|W) = 0.04

4% on Thursday, P(M|Th) = 0.04

8% on Monday, P(M|Mo) = 0.08

and 12% on Friday = P(M|F) = 0.12

The Company manufactures an equal amount of ball bearings (20 %) on each weekday, Hence, the probability that a random precision ball bearing was made on a particular day of the week, is mostly the same for all the five working days.

P(Mo) = 0.20

P(T) = 0.20

P(W) = 0.20

P(Th) = 0.20

P(F) 0.20

The probability that a defective ball bearing was manufactured on a Friday = P(F|M)

P(F|M) = P(F n M) ÷ P(M)

P(F n M) = P(M n F)

P(M) = P(Mo n M) + P(T n M) + P(W n M) + P(Th n M) + P(F n M)

We can obtain each of these probabilities by using the expression for conditional probability.

P(Mo n M) = P(M|Mo) × P(Mo) = 0.08 × 0.20 = 0.016

P(T n M) = P(M|T) × P(T) = 0.04 × 0.20 = 0.008

P(W n M) = P(M|W) × P(W) = 0.04 × 0.20 = 0.008

P(Th n M) = P(M|Th) × P(Th) = 0.04 × 0.20 = 0.008

P(F n M) = P(M|F) × P(F) = 0.12 × 0.20 = 0.024

P(M) = P(Mo n M) + P(T n M) + P(W n M) + P(Th n M) + P(F n M)

P(M) = 0.016 + 0.008 + 0.008 + 0 008 + 0.024 = 0.064

P(F|M) = P(F n M) ÷ P(M)

P(F n M) = P(M n F) = 0.024

P(M) = 0.064

P(F|M) = P(F n M) ÷ P(M) = (0.024/0.064) = 0.375

Hope this Helps!

4 0
2 years ago
Alice has seven times the amount of pens that Maurice has. Paul has two-thirds of the amount of pens as Alice and Suzy have comb
zepelin [54]

Answer:

Dawn has 32 pens.

Step-by-step explanation:

  • Let No. of pens Alice has = A
  • Let No. of pens Maurice has = M
  • Let no of pens Paul has = P
  • Let no. of pens Suzy has = S
  • Let no of pens Dawn has = D

Given :

  • A = 7M
  • P = 2/3 (A + S)  
  • D = P + 12
  • S = 1/2 M
  • If S = 2 {Given}
  • M = 4    [∵ S = 1/2 M → M = 2S = 2X(2) ]
  • A = 28  [ ∵ A = 7M → A = 7 x 4 ]
  • P = 20  [∵ P = 2/3 (A+S) → P = 2/3 (28 + 2) = 2/3 (30) ]
  • D = 32  [ ∵ D = P + 12 → D = 20 + 12 ]

5 0
1 year ago
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