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Date November 2016 Marks available 3 Reference code 16N.2.hl.TZ0.11
Level HL only Paper 2 Time zone TZ0
Command term Determine Question number 11 Adapted from N/A

Question

A Chocolate Shop advertises free gifts to customers that collect three vouchers. The vouchers are placed at random into 10% of all chocolate bars sold at this shop. Kati buys some of these bars and she opens them one at a time to see if they contain a voucher. Let \({\text{P}}(X = n)\) be the probability that Kati obtains her third voucher on the \(n{\text{th}}\) bar opened.

(It is assumed that the probability that a chocolate bar contains a voucher stays at 10% throughout the question.)

It is given that \({\text{P}}(X = n) = \frac{{{n^2} + an + b}}{{2000}} \times {0.9^{n - 3}}\) for \(n \geqslant 3,{\text{ }}n \in \mathbb{N}\).

Kati’s mother goes to the shop and buys \(x\) chocolate bars. She takes the bars home for Kati to open.

Show that \({\text{P}}(X = 3) = 0.001\) and \({\text{P}}(X = 4) = 0.0027\).

[3]
a.

Find the values of the constants \(a\) and \(b\).

[5]
b.

Deduce that \(\frac{{{\text{P}}(X = n)}}{{{\text{P}}(X = n - 1)}} = \frac{{0.9(n - 1)}}{{n - 3}}\) for \(n > 3\).

[4]
c.

(i)     Hence show that \(X\) has two modes \({m_1}\) and \({m_2}\).

(ii)     State the values of \({m_1}\) and \({m_2}\).

[5]
d.

Determine the minimum value of \(x\) such that the probability Kati receives at least one free gift is greater than 0.5.

[3]
e.

Markscheme

\({\text{P}}(X = 3) = {(0.1)^3}\)    A1

\( = 0.001\)    AG

\({\text{P}}(X = 4) = {\text{P}}(VV\bar VV) + {\text{P}}(V\bar VVV) + {\text{P}}(\bar VVVV)\)    (M1)

\( = 3 \times {(0.1)^3} \times 0.9\) (or equivalent)     A1

\( = 0.0027\)    AG

[3 marks]

a.

METHOD 1

attempting to form equations in \(a\) and \(b\)     M1

\(\frac{{9 + 3a + b}}{{2000}} = \frac{1}{{1000}}{\text{ }}(3a + b =  - 7)\)    A1

\(\frac{{16 + 4a + b}}{{2000}} \times \frac{9}{{10}} = \frac{{27}}{{10\,000}}{\text{ }}(4a + b =  - 10)\)    A1

attempting to solve simultaneously     (M1)

\(a =  - 3,{\text{ }}b = 2\)    A1

METHOD 2

\({\text{P}}(X = n) = \left( {\begin{array}{*{20}{c}} {n - 1} \\ 2 \end{array}} \right) \times {0.1^3} \times {0.9^{n - 3}}\)    M1

\( = \frac{{(n - 1)(n - 2)}}{{2000}} \times {0.9^{n - 3}}\)    (M1)A1

\( = \frac{{{n^2} - 3n + 2}}{{2000}} \times {0.9^{n - 3}}\)    A1

\(a =  - 3,b = 2\)    A1

 

Note: Condone the absence of \({0.9^{n - 3}}\) in the determination of the values of \(a\) and \(b\).

 

[5 marks]

b.

METHOD 1

EITHER

\({\text{P}}(X = n) = \frac{{{n^2} - 3n + 2}}{{2000}} \times {0.9^{n - 3}}\)    (M1)

OR

\({\text{P}}(X = n) = \left( {\begin{array}{*{20}{c}} {n - 1} \\ 2 \end{array}} \right) \times {0.1^3} \times {0.9^{n - 3}}\)    (M1)

THEN

\( = \frac{{(n - 1)(n - 2)}}{{2000}} \times {0.9^{n - 3}}\)    A1

\({\text{P}}(X = n - 1) = \frac{{(n - 2)(n - 3)}}{{2000}} \times {0.9^{n - 4}}\)    A1

\(\frac{{{\text{P}}(X = n)}}{{{\text{P}}(X = n - 1)}} = \frac{{(n - 1)(n - 2)}}{{(n - 2)(n - 3)}} \times 0.9\)    A1

\( = \frac{{0.9(n - 1)}}{{n - 3}}\)    AG

METHOD 2

\(\frac{{{\text{P}}(X = n)}}{{{\text{P}}(X = n - 1)}} = \frac{{\frac{{{n^2} - 3n + 2}}{{2000}} \times {{0.9}^{n - 3}}}}{{\frac{{{{(n - 1)}^2} - 3(n - 1) + 2}}{{2000}} \times {{0.9}^{n - 4}}}}\)    (M1)

\( = \frac{{0.9({n^2} - 3n + 2)}}{{({n^2} - 5n + 6)}}\)    A1A1

 

Note: Award A1 for a correct numerator and A1 for a correct denominator.

 

\( = \frac{{0.9(n - 1)(n - 2)}}{{(n - 2)(n - 3)}}\)    A1

\( = \frac{{0.9(n - 1)}}{{n - 3}}\)    AG

[4 marks]

c.

(i)     attempting to solve \(\frac{{0.9(n - 1)}}{{n - 3}} = 1\) for \(n\)     M1

\(n = 21\)    A1

\(\frac{{0.9(n - 1)}}{{n - 3}} < 1 \Rightarrow n > 21\)    R1

\(\frac{{0.9(n - 1)}}{{n - 3}} > 1 \Rightarrow n < 21\)    R1

\(X\) has two modes     AG

 

Note: Award R1R1 for a clearly labelled graphical representation of the two inequalities (using \(\frac{{{\text{P}}(X = n)}}{{{\text{P}}(X = n - 1)}}\)).

 

(ii)     the modes are 20 and 21     A1

[5 marks]

d.

METHOD 1

\(Y \sim {\text{B}}(x,{\text{ }}0.1)\)    (A1)

attempting to solve \({\text{P}}(Y \geqslant 3) > 0.5\) (or equivalent eg \(1 - {\text{P}}(Y \leqslant 2) > 0.5\)) for \(x\)     (M1)

 

Note: Award (M1) for attempting to solve an equality (obtaining \(x = 26.4\)).

 

\(x = 27\)    A1

METHOD 2

\(\sum\limits_{n = 0}^x {{\text{P}}(X = n) > 0.5} \)    (A1)

attempting to solve for \(x\)     (M1)

\(x = 27\)    A1

[3 marks]

e.

Examiners report

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Syllabus sections

Topic 5 - Core: Statistics and probability » 5.4 » Conditional probability; the definition \(P\left( {\left. A \right|P} \right) = \frac{{P\left( {A\mathop \cap \nolimits B} \right)}}{{P\left( B \right)}}\) .
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