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Question: The probability of throwing at most 2 sixes in 6 throws of a single die is \(\dfrac{a}{b}\cdot {{\le...

The probability of throwing at most 2 sixes in 6 throws of a single die is ab(56)4\dfrac{a}{b}\cdot {{\left( \dfrac{5}{6} \right)}^{4}}. Find a+ba+b. $$$$

Explanation

Solution

We see that the event of getting 6 in single throw of die is a Bernoulli’s trial with probability of success p=16p=\dfrac{1}{6} and failure q=56q=\dfrac{5}{6}. We use probability mass function of a random variable XX that takes number of as outcomes in binomial distribution P(X=k)=nCkpkqnk=nCkpk(1p)nkP\left( X=k \right)={}^{n}{{C}_{k}}{{p}^{k}}{{q}^{n-k}}={}^{n}{{C}_{k}}{{p}^{k}}{{\left( 1-p \right)}^{n-k}} to find P(X2)P\left( X\le 2 \right) to get ab(56)4\dfrac{a}{b}\cdot {{\left( \dfrac{5}{6} \right)}^{4}}.

Complete step-by-step solution:
We know that binomial distribution is a discrete probability distribution which takes number of successes in nn Bernoulli’s trials as outcomes with probability of success pp and probability failure q=1pq=1-p.If random variable XX follows binomial distribution (X ~B(n,p))\left( X\tilde{\ }B\left( n,p \right) \right) with number of trials nNn\in \mathsf{\mathbb{N}} and probability of success p[0,1]p\in \left[ 0,1 \right]the probability that we get kk successes in nn independent trials is given by the probability mass function,
P(X=k)=nCkpkqnk=nCkpk(1p)nkP\left( X=k \right)={}^{n}{{C}_{k}}{{p}^{k}}{{q}^{n-k}}={}^{n}{{C}_{k}}{{p}^{k}}{{\left( 1-p \right)}^{n-k}}
We are given the dice thrown 6 times. The probability of getting a 6 from the dice is p=16p=\dfrac{1}{6} and not getting 6 is q=56q=\dfrac{5}{6}. So we have p+q=16+56=1p+q=\dfrac{1}{6}+\dfrac{5}{6}=1. Hence the event of getting a six in a throw of single die is a Bernoulli’s trial. If we get a 6 in the trial it is success; otherwise failure. $$$$
We assign a random variable XX as which takes the number of times we get 6 as outcomes. We are asked to find the probability that we shall get at most 2 sixes which means we get either 0 six, 1 six or 2 sixes. So we have the required probability as

& P\left( X\le 2 \right) \\\ & \Rightarrow P\left( X=0 \right)+P\left( X=1 \right)+P\left( X=2 \right) \\\ \end{aligned}$$ We use the probability mass function for $p=\dfrac{1}{2},q=\dfrac{5}{6},n=6$ and $k=0,1,2$ respectively in the above step to have; $$\begin{aligned} & \Rightarrow {}^{6}{{C}_{0}}{{\left( \dfrac{1}{6} \right)}^{0}}{{\left( \dfrac{5}{6} \right)}^{6-0}}+{}^{6}{{C}_{1}}{{\left( \dfrac{1}{6} \right)}^{1}}{{\left( \dfrac{5}{6} \right)}^{6-1}}+{}^{6}{{C}_{2}}{{\left( \dfrac{1}{6} \right)}^{2}}{{\left( \dfrac{5}{6} \right)}^{6-2}} \\\ & \Rightarrow 1\times 1\cdot \times {{\left( \dfrac{5}{6} \right)}^{6}}+6\times \dfrac{1}{6}{{\left( \dfrac{5}{6} \right)}^{5}}+15\times \dfrac{1}{36}{{\left( \dfrac{5}{6} \right)}^{4}} \\\ & \Rightarrow {{\left( \dfrac{5}{6} \right)}^{6}}+{{\left( \dfrac{5}{6} \right)}^{5}}+\dfrac{5}{12}{{\left( \dfrac{5}{6} \right)}^{4}} \\\ \end{aligned}$$ We take ${{\left( \dfrac{5}{6} \right)}^{4}}$ common to have; $$\begin{aligned} & \Rightarrow {{\left( \dfrac{5}{6} \right)}^{4}}\left( \dfrac{25}{36}+\dfrac{5}{6}+\dfrac{5}{12} \right) \\\ & \Rightarrow {{\left( \dfrac{5}{6} \right)}^{4}}\left( \dfrac{25+30+15}{36} \right) \\\ & \Rightarrow {{\left( \dfrac{5}{6} \right)}^{4}}\left( \dfrac{70}{36} \right) \\\ \end{aligned}$$ We are given that the probability is $\dfrac{a}{b}\cdot {{\left( \dfrac{5}{6} \right)}^{4}}$. So we have the required answer as $$\begin{aligned} & {{\left( \dfrac{5}{6} \right)}^{4}}\left( \dfrac{70}{36} \right)=\dfrac{a}{b}\cdot {{\left( \dfrac{5}{6} \right)}^{4}} \\\ & \Rightarrow \dfrac{a}{b}=\dfrac{70}{36} \\\ & \Rightarrow a=70,b=36 \\\ & \Rightarrow a+b=70+36=106 \\\ \end{aligned}$$ **Note:** We note that we are not given in the question that $\dfrac{a}{b}$ is in simplest form otherwise $\dfrac{a}{b}=\dfrac{35}{18}$. We also note that a Bernoulli trial is a random experiment with exactly two possible outcomes called success or failure with probability of success does not change by repeating the experiment. Here in this problem we can either get 6 in a single throw of die or not get it at all. The expectation of binomial distribution is $np$ and the variance is $np\left( 1-p \right)$.