
A random variable X has the following probability distribution:
Determine
(i) \[k\]
(ii) $P(X < 3)$
(iii) $P(X > 6)$
(iv) $P(0 < X < 3)$
Answer
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Hint: In this question we will use the concept of probability distribution of a random variable. The probability distribution of random variable X is defined only when we have the various values of the random variable e.g. ${x_1},{x_2},{x_3},.......,{x_n}$together with respective probabilities ${p_1},{p_2},......,{p_n}$ satisfying $\sum\limits_{i = 1}^n {{p_i} = 1} $
Complete step-by-step answer:
(i) we know that the sum of all probabilities in a probability distribution is always unity. Therefore,
$
\Rightarrow P(X = 0) + P(X = 1) + P(X = 2) + ............. + P(X = 7) = 1 \\
\Rightarrow 0 + k + 2k + 2k + 3k + {k^2} + 2{k^2} + 7{k^2} + k = 1 \\
\Rightarrow 9k + 10{k^2} = 1 \\
\Rightarrow 10{k^2} + 9k - 1 = 0 \\
$
Now, after solving this equation, we get
$ \Rightarrow (10k - 1)(k + 1) = 0$.
$ \Rightarrow 10k - 1 = 0$ or $k + 1 = 0$
$
\Rightarrow 10k = 1 \\
\Rightarrow k = \dfrac{1}{{10}} \\
$ or $k = - 1$.
Hence, k = -1 cannot be possible because probability can’t be negative.
Therefore , $k = \dfrac{1}{{10}}$.
(ii) $P(X < 3)$.
$ \Rightarrow $ $P(X < 3)$= $P(X = 0) + P(X = 1) + P(X = 2)$.
$ \Rightarrow $ $P(X < 3)$= $0 + k + 2k$
$ \Rightarrow $ $P(X < 3)$= 3k
putting $k = \dfrac{1}{{10}}$, we get
$ \Rightarrow $ $P(X < 3)$ = $3 \times \dfrac{1}{{10}} = \dfrac{3}{{10}}$.
Hence, $P(X < 3)$ = $\dfrac{3}{{10}}$.
(iii) $P(X > 6)$.
$ \Rightarrow $ $P(X > 6)$ = $P(X = 7)$
$ \Rightarrow $ $P(X > 6)$ = $7{k^2} + k = 7 \times {\left( {\dfrac{1}{{10}}} \right)^2} + \dfrac{1}{{10}}$.
$ \Rightarrow $ $P(X > 6)$ = $\dfrac{7}{{100}} + \dfrac{1}{{10}} = \dfrac{{7 + 10}}{{100}}$
$ \Rightarrow $ $P(X > 6)$ = $\dfrac{{17}}{{100}}$.
Hence, $P(X > 6)$ = $\dfrac{{17}}{{100}}$.
(iv) $P(0 < X < 3)$.
$ \Rightarrow $ $P(0 < X < 3)$= $P(X = 1) + P(X = 2)$.
$ \Rightarrow $ $P(0 < X < 3)$= $k + 2k = 3k$
$ \Rightarrow $ $P(0 < X < 3)$= $3 \times \dfrac{1}{{10}} = \dfrac{3}{{10}}$
Hence , $P(0 < X < 3)$ = $\dfrac{3}{{10}}$.
Note: Whenever we are asked this type of question, first we have to remember the basic points of the probability distribution of a random variable. As according to the questions asked we will use the properties and formulae of probability distribution, we can easily solve them and we will get the required answers.
Complete step-by-step answer:
(i) we know that the sum of all probabilities in a probability distribution is always unity. Therefore,
$
\Rightarrow P(X = 0) + P(X = 1) + P(X = 2) + ............. + P(X = 7) = 1 \\
\Rightarrow 0 + k + 2k + 2k + 3k + {k^2} + 2{k^2} + 7{k^2} + k = 1 \\
\Rightarrow 9k + 10{k^2} = 1 \\
\Rightarrow 10{k^2} + 9k - 1 = 0 \\
$
Now, after solving this equation, we get
$ \Rightarrow (10k - 1)(k + 1) = 0$.
$ \Rightarrow 10k - 1 = 0$ or $k + 1 = 0$
$
\Rightarrow 10k = 1 \\
\Rightarrow k = \dfrac{1}{{10}} \\
$ or $k = - 1$.
Hence, k = -1 cannot be possible because probability can’t be negative.
Therefore , $k = \dfrac{1}{{10}}$.
(ii) $P(X < 3)$.
$ \Rightarrow $ $P(X < 3)$= $P(X = 0) + P(X = 1) + P(X = 2)$.
$ \Rightarrow $ $P(X < 3)$= $0 + k + 2k$
$ \Rightarrow $ $P(X < 3)$= 3k
putting $k = \dfrac{1}{{10}}$, we get
$ \Rightarrow $ $P(X < 3)$ = $3 \times \dfrac{1}{{10}} = \dfrac{3}{{10}}$.
Hence, $P(X < 3)$ = $\dfrac{3}{{10}}$.
(iii) $P(X > 6)$.
$ \Rightarrow $ $P(X > 6)$ = $P(X = 7)$
$ \Rightarrow $ $P(X > 6)$ = $7{k^2} + k = 7 \times {\left( {\dfrac{1}{{10}}} \right)^2} + \dfrac{1}{{10}}$.
$ \Rightarrow $ $P(X > 6)$ = $\dfrac{7}{{100}} + \dfrac{1}{{10}} = \dfrac{{7 + 10}}{{100}}$
$ \Rightarrow $ $P(X > 6)$ = $\dfrac{{17}}{{100}}$.
Hence, $P(X > 6)$ = $\dfrac{{17}}{{100}}$.
(iv) $P(0 < X < 3)$.
$ \Rightarrow $ $P(0 < X < 3)$= $P(X = 1) + P(X = 2)$.
$ \Rightarrow $ $P(0 < X < 3)$= $k + 2k = 3k$
$ \Rightarrow $ $P(0 < X < 3)$= $3 \times \dfrac{1}{{10}} = \dfrac{3}{{10}}$
Hence , $P(0 < X < 3)$ = $\dfrac{3}{{10}}$.
Note: Whenever we are asked this type of question, first we have to remember the basic points of the probability distribution of a random variable. As according to the questions asked we will use the properties and formulae of probability distribution, we can easily solve them and we will get the required answers.
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