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Mr. and Mrs. Doran have a genetic history such that the probability that a child being born to them with a certain trait is 0.41 . If they have six children, what is the probability that at least four of their six children will have that trait? Round your answer to the nearest thousandth.
Answer:

Mr. and Mrs. Doran have a genetic history such that the probability that a child being born to them with a certain trait is 00.4141 . If they have six children, what is the probability that at least four of their six children will have that trait? Round your answer to the nearest thousandth.\newlineAnswer:

Full solution

Q. Mr. and Mrs. Doran have a genetic history such that the probability that a child being born to them with a certain trait is 00.4141 . If they have six children, what is the probability that at least four of their six children will have that trait? Round your answer to the nearest thousandth.\newlineAnswer:
  1. Identify values nn, kk, pp: Identify the values of nn, kk, and pp for the binomial probability formula.\newlinen=6n = 6 (the number of children)\newlinep=0.41p = 0.41 (the probability of a child having the trait)\newlineWe want to find the probability of at least k=4k = 4 children having the trait, which means we need to calculate the probabilities for k=4k = 4, kk00, and kk11 and sum them up.
  2. Use binomial probability formula: Use the binomial probability formula P(X=k)=C(n,k)(p)k(1p)(nk)P(X = k) = C(n, k) \cdot (p)^k \cdot (1-p)^{(n-k)} to calculate the probability for k=4k = 4.\newlineP(X=4)=C(6,4)(0.41)4(10.41)(64)P(X = 4) = C(6, 4) \cdot (0.41)^4 \cdot (1-0.41)^{(6-4)}
  3. Calculate C(6,4)C(6, 4): Calculate the binomial coefficient C(6,4)C(6, 4).C(6,4)=6!4!(64)!C(6, 4) = \frac{6!}{4!(6 - 4)!}= (6×5×4×3×2×1)(4×3×2×1×2×1)\frac{(6 \times 5 \times 4 \times 3 \times 2 \times 1)}{(4 \times 3 \times 2 \times 1 \times 2 \times 1)}= 6×52\frac{6 \times 5}{2}= 1515
  4. Calculate (0.41)4(0.41)^4: Calculate (0.41)4(0.41)^4.(0.41)4=0.41×0.41×0.41×0.41=0.0282401(0.41)^4 = 0.41 \times 0.41 \times 0.41 \times 0.41 = 0.0282401
  5. Calculate (10.41)(64)(1 - 0.41)^{(6 - 4)}: Calculate (10.41)(64)(1 - 0.41)^{(6 - 4)}.\newline(10.41)(64)=(0.59)2(1 - 0.41)^{(6 - 4)} = (0.59)^2\newline=0.3481= 0.3481
  6. Multiply values for P(X=4)P(X = 4): Multiply the values together to find P(X=4)P(X = 4).P(X=4)=15×0.0282401×0.3481=0.147651615P(X = 4) = 15 \times 0.0282401 \times 0.3481 = 0.147651615
  7. Repeat for k=5k = 5 and k=6k = 6: Repeat the process for k=5k = 5 and k=6k = 6. First, calculate P(X=5)P(X = 5) using the binomial probability formula. P(X=5)=C(6,5)(0.41)5(10.41)65P(X = 5) = C(6, 5) \cdot (0.41)^5 \cdot (1-0.41)^{6-5}
  8. Calculate C(6,5)C(6, 5): Calculate the binomial coefficient C(6,5)C(6, 5).C(6,5)=6!5!(65)!=6C(6, 5) = \frac{6!}{5!(6 - 5)!} = 6
  9. Calculate (0.41)5(0.41)^5: Calculate (0.41)5(0.41)^5.(0.41)5=0.41×0.41×0.41×0.41×0.41=0.01155761(0.41)^5 = 0.41 \times 0.41 \times 0.41 \times 0.41 \times 0.41 = 0.01155761
  10. Calculate (10.41)(65)(1 - 0.41)^{(6 - 5)}: Calculate (10.41)(65)(1 - 0.41)^{(6 - 5)}.(10.41)(65)=(0.59)1(1 - 0.41)^{(6 - 5)} = (0.59)^1=0.59= 0.59
  11. Multiply values for P(X=5)P(X = 5): Multiply the values together to find P(X=5)P(X = 5).P(X=5)=6×0.01155761×0.59=0.040930806P(X = 5) = 6 \times 0.01155761 \times 0.59 = 0.040930806
  12. Calculate P(X=6)P(X = 6): Finally, calculate P(X=6)P(X = 6) using the binomial probability formula.\newlineP(X=6)=C(6,6)(0.41)6(10.41)66P(X = 6) = C(6, 6) \cdot (0.41)^6 \cdot (1-0.41)^{6-6}
  13. Calculate C(6,6)C(6, 6): Calculate the binomial coefficient C(6,6)C(6, 6).C(6,6)=6!6!(66)!=1C(6, 6) = \frac{6!}{6!(6 - 6)!} = 1
  14. Calculate (0.41)6(0.41)^6: Calculate (0.41)6(0.41)^6.(0.41)6=0.41×0.41×0.41×0.41×0.41×0.41=0.004665641(0.41)^6 = 0.41 \times 0.41 \times 0.41 \times 0.41 \times 0.41 \times 0.41 = 0.004665641
  15. Calculate (10.41)(66)(1 - 0.41)^{(6 - 6)}: Calculate (10.41)(66)(1 - 0.41)^{(6 - 6)}.\newline(10.41)(66)=(0.59)0(1 - 0.41)^{(6 - 6)} = (0.59)^0\newline=1= 1
  16. Multiply values for P(X=6)P(X = 6): Multiply the values together to find P(X=6)P(X = 6).P(X=6)=1×0.004665641×1=0.004665641P(X = 6) = 1 \times 0.004665641 \times 1 = 0.004665641
  17. Sum probabilities for at least 44: Sum the probabilities P(X=4)P(X = 4), P(X=5)P(X = 5), and P(X=6)P(X = 6) to find the total probability of at least four children having the trait.\newlineP(at least 4)=P(X=4)+P(X=5)+P(X=6)P(\text{at least 4}) = P(X = 4) + P(X = 5) + P(X = 6)\newline=0.147651615+0.040930806+0.004665641= 0.147651615 + 0.040930806 + 0.004665641\newline=0.193248062= 0.193248062
  18. Round final probability: Round the final probability to the nearest thousandth. P(at least 4)=0.193P(\text{at least } 4) = 0.193

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