IBDP Maths analysis and approaches Topic: SL 3.13 Mutually exclusive events HL Paper 1

Question

On Saturday, Alfred and Beatrice play 6 different games against each other. In each game, one of the two wins. The probability that Alfred wins any one of these games is \(\frac{2}{3}\).

a.Show that the probability that Alfred wins exactly 4 of the games is \(\frac{{80}}{{243}}\).[3]

 

(i)     Explain why the total number of possible outcomes for the results of the 6 games is 64.

(ii)     By expanding \({(1 + x)^6}\) and choosing a suitable value for x, prove

\[64 = \left( {\begin{array}{*{20}{c}}
  6 \\
  0
\end{array}} \right) + \left( {\begin{array}{*{20}{c}}
  6 \\
  1
\end{array}} \right) + \left( {\begin{array}{*{20}{c}}
  6 \\
  2
\end{array}} \right) + \left( {\begin{array}{*{20}{c}}
  6 \\
  3
\end{array}} \right) + \left( {\begin{array}{*{20}{c}}
  6 \\
  4
\end{array}} \right) + \left( {\begin{array}{*{20}{c}}
  6 \\
  5
\end{array}} \right) + \left( {\begin{array}{*{20}{c}}
  6 \\
  6
\end{array}} \right)\]

b.(iii)     State the meaning of this equality in the context of the 6 games played.[4]

 

The following day Alfred and Beatrice play the 6 games again. Assume that the probability that Alfred wins any one of these games is still \(\frac{2}{3}\).

(i)     Find an expression for the probability Alfred wins 4 games on the first day and 2 on the second day. Give your answer in the form \({\left( {\begin{array}{*{20}{c}}
  6 \\
  r
\end{array}} \right)^2}{\left( {\frac{2}{3}} \right)^s}{\left( {\frac{1}{3}} \right)^t}\) where the values of r, s and t are to be found.

(ii)     Using your answer to (c) (i) and 6 similar expressions write down the probability that Alfred wins a total of 6 games over the two days as the sum of 7 probabilities.

(iii)     Hence prove that \(\left( {\begin{array}{*{20}{c}}
  {12} \\
  6
\end{array}} \right) = {\left( {\begin{array}{*{20}{c}}
  6 \\
  0
\end{array}} \right)^2} + {\left( {\begin{array}{*{20}{c}}
  6 \\
  1
\end{array}} \right)^2} + {\left( {\begin{array}{*{20}{c}}
  6 \\
  2
\end{array}} \right)^2} + {\left( {\begin{array}{*{20}{c}}
  6 \\
  3
\end{array}} \right)^2} + {\left( {\begin{array}{*{20}{c}}
  6 \\
  4
\end{array}} \right)^2} + {\left( {\begin{array}{*{20}{c}}
  6 \\
  5
\end{array}} \right)^2} + {\left( {\begin{array}{*{20}{c}}
  6 \\
  6
\end{array}} \right)^2}\).
[9]

c.

Alfred and Beatrice play n games. Let A denote the number of games Alfred wins. The expected value of A can be written as \({\text{E}}(A) = \sum\limits_{r = 0}^n {r\left( {\begin{array}{*{20}{c}}
  n \\
  r
\end{array}} \right)} \frac{{{a^r}}}{{{b^n}}}\).

d.(i)     Find the values of a and b.

(ii)     By differentiating the expansion of \({(1 + x)^n}\), prove that the expected number of games Alfred wins is \(\frac{{2n}}{3}\).[6]

 
▶️Answer/Explanation

Markscheme

\(B\left( {6,\frac{2}{3}} \right)\)     (M1)

\(p(4) = \left( {\begin{array}{*{20}{c}}
  6 \\
  4
\end{array}} \right){\left( {\frac{2}{3}} \right)^4}{\left( {\frac{1}{3}} \right)^2}\)     A1

\(\left( {\begin{array}{*{20}{c}}
  6 \\
  4
\end{array}} \right) = 15\)     A1

\( = 15 \times \frac{{{2^4}}}{{{3^6}}} = \frac{{80}}{{243}}\)     AG

[3 marks]

a.

(i)     2 outcomes for each of the 6 games or \({2^6} = 64\)     R1

 

(ii)     \({(1 + x)^6} = \left( {\begin{array}{*{20}{c}}
  6 \\
  0
\end{array}} \right) + \left( {\begin{array}{*{20}{c}}
  6 \\
  1
\end{array}} \right)x + \left( {\begin{array}{*{20}{c}}
  6 \\
  2
\end{array}} \right){x^2} + \left( {\begin{array}{*{20}{c}}
  6 \\
  3
\end{array}} \right){x^3} + \left( {\begin{array}{*{20}{c}}
  6 \\
  4
\end{array}} \right){x^4} + \left( {\begin{array}{*{20}{c}}
  6 \\
  5
\end{array}} \right){x^5} + \left( {\begin{array}{*{20}{c}}
  6 \\
  6
\end{array}} \right){x^6}\)     A1

Note: Accept \(^n{C_r}\) notation or \(1 + 6x + 15{x^2} + 20{x^3} + 15{x^4} + 6{x^5} + {x^6}\)

setting x = 1 in both sides of the expression     R1

Note: Do not award R1 if the right hand side is not in the correct form.

 

\(64 = \left( {\begin{array}{*{20}{c}}
  6 \\
  0
\end{array}} \right) + \left( {\begin{array}{*{20}{c}}
  6 \\
  1
\end{array}} \right) + \left( {\begin{array}{*{20}{c}}
  6 \\
  2
\end{array}} \right) + \left( {\begin{array}{*{20}{c}}
  6 \\
  3
\end{array}} \right) + \left( {\begin{array}{*{20}{c}}
  6 \\
  4
\end{array}} \right) + \left( {\begin{array}{*{20}{c}}
  6 \\
  5
\end{array}} \right) + \left( {\begin{array}{*{20}{c}}
  6 \\
  6
\end{array}} \right)\)     AG

 

(iii)     the total number of outcomes = number of ways Alfred can win no games, plus the number of ways he can win one game etc.     R1 

[4 marks]

b.

(i)     Let \({\text{P}}(x,{\text{ }}y)\) be the probability that Alfred wins x games on the first day and y on the second.

\({\text{P(4, 2)}} = \left( {\begin{array}{*{20}{c}}
  6 \\
  4
\end{array}} \right) \times {\left( {\frac{2}{3}} \right)^4} \times {\left( {\frac{1}{3}} \right)^2} \times \left( {\begin{array}{*{20}{c}}
  6 \\
  2
\end{array}} \right) \times {\left( {\frac{2}{3}} \right)^2} \times {\left( {\frac{1}{3}} \right)^4}\)     M1A1

\({\left( {\begin{array}{*{20}{c}}
  6 \\
  2
\end{array}} \right)^2}{\left( {\frac{2}{3}} \right)^6}{\left( {\frac{1}{3}} \right)^6}\) or \({\left( {\begin{array}{*{20}{c}}
  6 \\
  4
\end{array}} \right)^2}{\left( {\frac{2}{3}} \right)^6}{\left( {\frac{1}{3}} \right)^6}\)     A1

r = 2 or 4, s = t = 6

 

(ii)     P(Total = 6) =

P(0, 6) + P(1, 5) + P(2, 4) + P(3, 3) + P(4, 2) + P(5, 1) + P(6, 0)     (M1)

\( = {\left( {\begin{array}{*{20}{c}}
  6 \\
  0
\end{array}} \right)^2}{\left( {\frac{2}{3}} \right)^6}{\left( {\frac{1}{3}} \right)^6} + {\left( {\begin{array}{*{20}{c}}
  6 \\
  1
\end{array}} \right)^2}{\left( {\frac{2}{3}} \right)^6}{\left( {\frac{1}{3}} \right)^6} + … + {\left( {\begin{array}{*{20}{c}}
  6 \\
  6
\end{array}} \right)^2}{\left( {\frac{2}{3}} \right)^6}{\left( {\frac{1}{3}} \right)^6}\)     A2

\( = \frac{{{2^6}}}{{{3^{12}}}}\left( {{{\left( {\begin{array}{*{20}{c}}
  6 \\
  0
\end{array}} \right)}^2} + {{\left( {\begin{array}{*{20}{c}}
  6 \\
  1
\end{array}} \right)}^2} + {{\left( {\begin{array}{*{20}{c}}
  6 \\
  2
\end{array}} \right)}^2} + {{\left( {\begin{array}{*{20}{c}}
  6 \\
  3
\end{array}} \right)}^2} + {{\left( {\begin{array}{*{20}{c}}
  6 \\
  4
\end{array}} \right)}^2} + {{\left( {\begin{array}{*{20}{c}}
  6 \\
  5
\end{array}} \right)}^2} + {{\left( {\begin{array}{*{20}{c}}
  6 \\
  6
\end{array}} \right)}^2}} \right)\)

Note: Accept any valid sum of 7 probabilities.

 

(iii)     use of \(\left( {\begin{array}{*{20}{c}}
  6 \\
  i
\end{array}} \right) = \left( {\begin{array}{*{20}{l}}
  6 \\
  {6 – i}
\end{array}} \right)\)     (M1)

(can be used either here or in (c)(ii))

P(wins 6 out of 12) \( = \left( {\begin{array}{*{20}{c}}
  {12} \\
  6
\end{array}} \right) \times {\left( {\frac{2}{3}} \right)^6} \times {\left( {\frac{1}{3}} \right)^6} = \frac{{{2^6}}}{{{3^{12}}}}\left( {\begin{array}{*{20}{c}}
  {12} \\
  6
\end{array}} \right)\)     A1

\( = \frac{{{2^6}}}{{{3^{12}}}}\left( {{{\left( {\begin{array}{*{20}{c}}
  6 \\
  0
\end{array}} \right)}^2} + {{\left( {\begin{array}{*{20}{c}}
  6 \\
  1
\end{array}} \right)}^2} + {{\left( {\begin{array}{*{20}{c}}
  6 \\
  2
\end{array}} \right)}^2} + {{\left( {\begin{array}{*{20}{c}}
  6 \\
  3
\end{array}} \right)}^2} + {{\left( {\begin{array}{*{20}{c}}
  6 \\
  4
\end{array}} \right)}^2} + {{\left( {\begin{array}{*{20}{c}}
  6 \\
  5
\end{array}} \right)}^2} + {{\left( {\begin{array}{*{20}{c}}
  6 \\
  6
\end{array}} \right)}^2}} \right) = \frac{{{2^6}}}{{{3^{12}}}}\left( {\begin{array}{*{20}{c}}
  {12} \\
  6
\end{array}} \right)\)     A1

therefore \({\left( {\begin{array}{*{20}{c}}
  6 \\
  0
\end{array}} \right)^2} + {\left( {\begin{array}{*{20}{c}}
  6 \\
  1
\end{array}} \right)^2} + {\left( {\begin{array}{*{20}{c}}
  6 \\
  2
\end{array}} \right)^2} + {\left( {\begin{array}{*{20}{c}}
  6 \\
  3
\end{array}} \right)^2} + {\left( {\begin{array}{*{20}{c}}
  6 \\
  4
\end{array}} \right)^2} + {\left( {\begin{array}{*{20}{c}}
  6 \\
  5
\end{array}} \right)^2} + {\left( {\begin{array}{*{20}{c}}
  6 \\
  6
\end{array}} \right)^2} = \left( {\begin{array}{*{20}{c}}
  {12} \\
  6
\end{array}} \right)\)     AG

[9 marks]

c.

(i)     \({\text{E}}(A) = \sum\limits_{r = 0}^n {r\left( {\begin{array}{*{20}{c}}
  n \\
  r
\end{array}} \right)} {\left( {\frac{2}{3}} \right)^r}{\left( {\frac{1}{3}} \right)^{n – r}} = \sum\limits_{r = 0}^n {r\left( {\begin{array}{*{20}{c}}
  n \\
  r
\end{array}} \right)} \frac{{{2^r}}}{{{3^n}}}\)

(a = 2, b = 3)     M1A1

Note: M0A0 for a = 2, b = 3 without any method.

(ii)     \(n{(1 + x)^{n – 1}} = \sum\limits_{r = 1}^n {\left( {\begin{array}{*{20}{c}}
  n \\
  r
\end{array}} \right)} r{x^{r – 1}}\)     A1A1

(sigma notation not necessary)

(if sigma notation used also allow lower limit to be r = 0)

let x = 2     M1

\(n{3^{n – 1}} = \sum\limits_{r = 1}^n {\left( {\begin{array}{*{20}{c}}
  n \\
  r
\end{array}} \right)} r{2^{r – 1}}\)

multiply by 2 and divide by \({3^n}\)     (M1)

\(\frac{{2n}}{3} = \sum\limits_{r = 1}^n {\left( {\begin{array}{*{20}{c}}
  n \\
  r
\end{array}} \right)} r\frac{{{2^r}}}{{{3^n}}}\left( { = \sum\limits_{r = 0}^n {\left( {\begin{array}{*{20}{c}}
  n \\
  r
\end{array}} \right)} \frac{{{2^r}}}{{{3^n}}}} \right)\)     AG

[6 marks]

d.

Question

Tim and Caz buy a box of 16 chocolates of which 10 are milk and 6 are dark. Caz randomly takes a chocolate and eats it. Then Tim randomly takes a chocolate and eats it.

a.Draw a tree diagram representing the possible outcomes, clearly labelling each branch with the correct probability.[3]

 

b.Find the probability that Tim and Caz eat the same type of chocolate.[2]

 
▶️Answer/Explanation

Markscheme

     A1A1A1

[3 marks]

Note: Award A1 for the initial level probabilities, A1 for each of the second level branch probabilities.

a.

\(\frac{{10}}{{16}} \times \frac{9}{{15}} + \frac{6}{{16}} \times \frac{5}{{15}}\)     (M1)

\( = \frac{{120}}{{240}}{\text{ }}\left( { = \frac{1}{2}} \right)\)     A1

[2 marks]

b.

Examiners report

Generally well done. A few candidates didn’t take account of the fact that Caz ate the chocolate, so didn’t replace it. A few candidates made arithmetic errors in calculating the probability.

a.

Generally well done. A few candidates didn’t take account of the fact that Caz ate the chocolate, so didn’t replace it. A few candidates made arithmetic errors in calculating the probability.

b.

Question

A football team, Melchester Rovers are playing a tournament of five matches.

The probabilities that they win, draw or lose a match are \(\frac{1}{2}\), \(\frac{1}{6}\) and \(\frac{1}{3}\) respectively.

These probabilities remain constant; the result of a match is independent of the results of other matches. At the end of the tournament their coach Roy loses his job if they lose three consecutive matches, otherwise he does not lose his job. Find the probability that Roy loses his job.

▶️Answer/Explanation

Markscheme

METHOD 1

to have \(3\) consecutive losses there must be exactly \(5\), \(4\) or \(3\) losses

the probability of exactly \(5\) losses (must be \(3\) consecutive) is \({\left( {\frac{1}{3}} \right)^5}\)     A1

the probability of exactly \(4\) losses (with \(3\) consecutive) is \(4{\left( {\frac{1}{3}} \right)^4}\left( {\frac{2}{3}} \right)\)     A1A1

Note:     First A1 is for the factor \(4\) and second A1 for the other \(2\) factors.

the probability of exactly \(3\) losses (with \(3\) consecutive) is \(3{\left( {\frac{1}{3}} \right)^3}{\left( {\frac{2}{3}} \right)^2}\)     A1A1

Note:     First A1 is for the factor \(3\) and second A1 for the other \(2\) factors.

(Since the events are mutually exclusive)

the total probability is \(\frac{{1 + 8 + 12}}{{{3^5}}} = \frac{{21}}{{243}}\;\;\;\left( { = \frac{7}{{81}}} \right)\)     A1

[6 marks]

METHOD 2

Roy loses his job if

A – first \(3\) games are all lost (so the last \(2\) games can be any result)

B – first \(3\) games are not all lost, but middle \(3\) games are all lost (so the first game is not a loss and the last game can be any result)

or C – first \(3\) games are not all lost, middle \(3\) games are not all lost but last \(3\) games are all lost, (so the first game can be any result but the second game is not a loss)

for A \({4^{{\text{th}}}}\) & \({5^{{\text{th}}}}\) games can be anything

\({\text{P}}(A) = {\left( {\frac{1}{3}} \right)^3} = \frac{1}{{27}}\)     A1

for B \({1^{{\text{st}}}}\) game not a loss & \({5^{{\text{th}}}}\) game can be anything     (R1)

\({\text{P}}(B) = \frac{2}{3} \times {\left( {\frac{1}{3}} \right)^3} = \frac{2}{{81}}\)     A1

for C \({1^{{\text{st}}}}\) game anything, \({2^{{\text{nd}}}}\) game not a loss     (R1)

\({\text{P}}(C) = 1 \times \frac{2}{3} \times {\left( {\frac{1}{3}} \right)^3} = \frac{2}{{81}}\)     A1

(Since the events are mutually exclusive)

total probability is \(\frac{1}{{27}} + \frac{2}{{81}} + \frac{2}{{81}} = \frac{7}{{81}}\)     A1

Note:     In both methods all the A marks are independent.

Note:     If the candidate misunderstands the question and thinks that it is asking for exactly \(3\) losses award A1 A1 and A1 for an answer of \(\frac{{12}}{{243}}\) as in the last lines of Method 1.

[6 marks]

Total [6 marks]

Examiners report

If a script has lots of numbers with the wrong final answer and no explanation of method it is not going to gain many marks. Working has to be explained. The counting strategy needs to be decided on first. Some candidates misunderstood the context and tried to calculate exactly \(3\) consecutive losses. Not putting a non-loss as \(\frac{2}{3}\) caused unnecessary work.

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