(a) \mathrm P(X=1)=\dfrac3{10} (A1); \mathrm P(X=2)=\dfrac7{10}\times\dfrac39=\dfrac7{30} (A1); \mathrm P(X=3)=\dfrac7{10}\times\dfrac69\times\dfrac38=\dfrac7{40} (A1).
(b) The positions of the 3 red balls form a random 3-element subset of \{1,\dots,10\}, all subsets equally likely (M1); Number of equally likely subsets =\dbinom{10}3 (A1); X=k: position k is red, positions 1,\dots,k-1 are blue, and the other two red balls lie among the 10-k later positions (M1); Number of favourable subsets =\dbinom{10-k}2 (A1); \mathrm P(X=k)=\dfrac{\binom{10-k}2}{\binom{10}3}, k=1,\dots,8 (AG).
(c) \mathrm E(X)=\displaystyle\sum_{k=1}^{8}k\,\mathrm P(X=k) (M1); \mathrm P(X=k)=\dfrac{36}{120},\dfrac{28}{120},\dfrac{21}{120},\dfrac{15}{120},\dfrac{10}{120},\dfrac6{120},\dfrac3{120},\dfrac1{120} (A1); \mathrm E(X)=\dfrac{330}{120}=\dfrac{11}4 (A1).
(d) With replacement, X is geometric with p=\dfrac3{10}: \mathrm E(X)=\dfrac1p=\dfrac{10}3 (3.33) (A1); Larger than \dfrac{11}4: without replacement each blue ball removed raises the chance of a red next time, so waits are shorter (and cannot exceed 8) (R1).
(e) Generalise (b): \mathrm P(X=k)=\dfrac{\binom{r+b-k}{r-1}}{\binom{r+b}r}; sum k\,\mathrm P(X=k) for small cases (M1); (r,b)=(1,1): \dfrac32; (1,2): 2; (2,2): \dfrac53; (2,3): 2; (3,7): \dfrac{11}4 (A1); Conjecture: \mathrm E(X)=\dfrac{r+b+1}{r+1} (A1).
(f) r=1: the red ball is equally likely to be in each of the b+1 positions, so \mathrm P(X=k)=\dfrac1{b+1}, k=1,\dots,b+1 (A1); \mathrm E(X)=\dfrac1{b+1}\displaystyle\sum_{k=1}^{b+1}k=\dfrac1{b+1}\times\dfrac{(b+1)(b+2)}2 (M1); =\dfrac{b+2}2=\dfrac{r+b+1}{r+1} when r=1 (A1).
(g) \mathrm P(T>t)=\displaystyle\int_t^\infty\lambda e^{-\lambda u}\,\mathrm du=\left[-e^{-\lambda u}\right]_t^\infty (M1); e^{-\lambda u}\to0 as u\to\infty, so \mathrm P(T>t)=e^{-\lambda t} (A1); \mathrm P(T>s+t\mid T>s)=\dfrac{\mathrm P(T>s+t)}{\mathrm P(T>s)} (M1); =\dfrac{e^{-\lambda(s+t)}}{e^{-\lambda s}}=e^{-\lambda t}=\mathrm P(T>t) (AG); The chance of waiting a further t minutes does not depend on how long you have already waited (memoryless) (R1).
(h) \mathrm E(T)=\displaystyle\int_0^\infty t\,\lambda e^{-\lambda t}\,\mathrm dt (M1); By parts with u=t, \dfrac{\mathrm dv}{\mathrm dt}=\lambda e^{-\lambda t}: \left[-te^{-\lambda t}\right]_0^\infty+\displaystyle\int_0^\infty e^{-\lambda t}\,\mathrm dt (M1 A1); te^{-\lambda t}\to0 as t\to\infty, so the bracket is 0 (A1); \mathrm E(T)=\left[-\dfrac1\lambda e^{-\lambda t}\right]_0^\infty=\dfrac1\lambda (AG).
(i) Median m: \mathrm P(T>m)=\dfrac12\Rightarrow e^{-\lambda m}=\dfrac12 (M1); m=\dfrac{\ln2}\lambda\approx\dfrac{0.693}\lambda, which is less than the mean \dfrac1\lambda: the distribution is skewed to the right (A1).
(j) Timetabled buses get more likely to arrive as the wait grows; the model says the wait ahead is the same however long you have waited (R1); The density is greatest at t=0 and has no upper limit, while timetabled gaps cluster near the scheduled interval and are bounded (R1).
Final answer
Paper A3, Question 2. (a) \tfrac3{10},\ \tfrac7{30},\ \tfrac7{40}; (b) proof; (c) \tfrac{11}4; (d) \tfrac{10}3, larger; (e) \dfrac{r+b+1}{r+1}; (f) proof; (g) proof, memoryless; (h) proof; (i) median \dfrac{\ln2}\lambda, below the mean; (j) not realistic: timetabled buses are not memoryless.