Date | November 2017 | Marks available | 3 | Reference code | 17N.3sp.hl.TZ0.5 |
Level | HL only | Paper | Paper 3 Statistics and probability | Time zone | TZ0 |
Command term | Show that | Question number | 5 | Adapted from | N/A |
Question
The random variable X follows a Poisson distribution with mean λ. The probability generating function of X is given by GX(t)=eλ(t−1).
The random variable Y, independent of X, follows a Poisson distribution with mean μ.
Find expressions for G′X(t) and GX″.
Hence show that {\text{Var}}(X) = \lambda .
By considering the probability generating function, {G_{X + Y}}(t), of X + Y, show that X + Y follows a Poisson distribution with mean \lambda + \mu .
Show that {\text{P}}(X = x|X + Y = n) = \left( {\begin{array}{*{20}{c}} n \\ x \end{array}} \right){\left( {\frac{\lambda }{{\lambda + \mu }}} \right)^x}{\left( {1 - \frac{\lambda }{{\lambda + \mu }}} \right)^{n - x}}, where n, x are non-negative integers and n \geqslant x.
Identify the probability distribution given in part (c)(i) and state its parameters.
Markscheme
{G’_X}(t) = \lambda {{\text{e}}^{\lambda (t - 1)}} A1
{G’’_X}(t) = {\lambda ^2}{{\text{e}}^{\lambda (t - 1)}} A1
[2 marks]
{\text{Var}}(X) = {G''_X}(1) + {G'_X}(1) - {\left( {{{G'}_X}(1)} \right)^2} (M1)
{G’_X}(1) = \lambda and {G’’_X}(1) = {\lambda ^2} (A1)
{\text{Var}}(X) = {\lambda ^2} + \lambda - {\lambda ^2} A1
= \lambda AG
[3 marks]
{G_{X + Y}}(t) = {{\text{e}}^{\lambda (t - 1)}} \times {{\text{e}}^{\mu (t - 1)}} M1
Note: The M1 is for knowing to multiply pgfs.
= {{\text{e}}^{(\lambda + \mu )(t - 1)}} A1
which is the pgf for a Poisson distribution with mean \lambda + \mu R1AG
Note: Line 3 identifying the Poisson pgf must be seen.
[3 marks]
{\text{P}}(X = x|X + Y = n) = \frac{{{\text{P}}(X = x \cap Y = n - x)}}{{{\text{P}}(X + Y = n)}} (M1)
= \left( {\frac{{{{\text{e}}^{ - \lambda }}{\lambda ^x}}}{{x!}}} \right)\left( {\frac{{{{\text{e}}^{ - \mu }}{\mu ^{n - x}}}}{{(n - x)!}}} \right)\left( {\frac{{n!}}{{{{\text{e}}^{ - (\lambda + \mu )}}{{(\lambda + \mu )}^n}}}} \right) (or equivalent) M1A1
= \left( {\begin{array}{*{20}{c}} n \\ x \end{array}} \right)\frac{{{\lambda ^x}{\mu ^{n - x}}}}{{{{(\lambda + \mu )}^n}}} A1
= \left( {\begin{array}{*{20}{c}} n \\ x \end{array}} \right){\left( {\frac{\lambda }{{\lambda + \mu }}} \right)^x}{\left( {\frac{\mu }{{\lambda + \mu }}} \right)^{n - x}} A1
leading to {\text{P}}(X = x|X + Y = n) = \left( {\begin{array}{*{20}{c}} n \\ x \end{array}} \right){\left( {\frac{\lambda }{{\lambda + \mu }}} \right)^x}{\left( {1 - \frac{\lambda }{{\lambda + \mu }}} \right)^{n - x}} AG
[5 marks]
{\text{B}}\left( {n,{\text{ }}\frac{\lambda }{{\lambda + \mu }}} \right) A1A1
Note: Award A1 for stating binomial and A1 for stating correct parameters.
[2 marks]