Date | None Specimen | Marks available | 5 | Reference code | SPNone.2.hl.TZ0.12 |
Level | HL only | Paper | 2 | Time zone | TZ0 |
Command term | Calculate and Determine | Question number | 12 | Adapted from | N/A |
Question
The weights, in kg, of male birds of a certain species are modelled by a normal distribution with mean μ and standard deviation σ .
Given that 70 % of the birds weigh more than 2.1 kg and 25 % of the birds weigh more than 2.5 kg, calculate the value of μ and the value of σ .
A random sample of ten of these birds is obtained. Let X denote the number of birds in the sample weighing more than 2.5 kg.
(i) Calculate E(X) .
(ii) Calculate the probability that exactly five of these birds weigh more than 2.5 kg.
(iii) Determine the most likely value of X .
The number of eggs, Y , laid by female birds of this species during the nesting season is modelled by a Poisson distribution with mean λ . You are given that P(Y⩾ , correct to 5 decimal places.
(i) Determine the value of \lambda .
(ii) Calculate the probability that two randomly chosen birds lay a total of
two eggs between them.
(iii) Given that the two birds lay a total of two eggs between them, calculate the probability that they each lay one egg.
Markscheme
we are given that
2.1 = \mu - 0.5244\sigma
2.5 = \mu + 0.6745\sigma M1A1
\mu = 2.27{\text{ , }}\sigma = 0.334 A1A1
[4 marks]
(i) let X denote the number of birds weighing more than 2.5 kg
then X is B(10, 0.25) A1
{\text{E}}(X) = 2.5 A1
(ii) 0.0584 A1
(iii) to find the most likely value of X , consider
{p_0} = 0.0563 \ldots ,{\text{ }}{p_1} = 0.1877 \ldots ,{\text{ }}{p_2} = 0.2815 \ldots ,{\text{ }}{p_3} = 0.2502 \ldots M1
therefore, most likely value = 2 A1
[5 marks]
(i) we solve 1 - {\text{P}}(Y \leqslant 1) = 0.80085 using the GDC M1
\lambda = 3.00 A1
(ii) let {X_1}{\text{, }}{X_2} denote the number of eggs laid by each bird
{\text{P}}({X_1} + {X_2} = 2) = {\text{P}}({X_1} = 0){\text{P}}({X_2} = 1) + {\text{P}}({X_1} = 1){\text{P}}({X_2} = 1) + {\text{P}}({X_1} = 2){\text{P}}({X_2} = 0) M1A1
= {{\text{e}}^{ - 3}} \times {{\text{e}}^{ - 3}} \times \frac{9}{2} + {({{\text{e}}^{ - 3}} \times 3)^2} + {{\text{e}}^{ - 3}} \times \frac{9}{2} \times {{\text{e}}^{ - 3}} = 0.0446 A1
(iii) {\text{P}}({X_1} = 1,{\text{ }}{X_2} = 1|{X_1} + {X_2} = 2) = \frac{{{\text{P}}({X_1} = 1,{\text{ }}{X_2} = 1)}}{{{\text{P}}({X_1} + {X_2} = 2)}} M1A1
= 0.5 A1
[8 marks]