
A continuous random variable X has the P.D.F $f\left( x \right)=3{{x}^{2}},0\le x\le 1$. The value of a constant $\lambda $ that satisfies the relation $P\left\{ X\le \lambda \right\}=P\left\{ X>\lambda \right\}$ is
A. ${{\left( \dfrac{1}{3} \right)}^{\dfrac{1}{2}}}$
B. ${{\left( \dfrac{1}{2} \right)}^{\dfrac{1}{3}}}$
C. ${{\left( \dfrac{2}{3} \right)}^{\dfrac{1}{2}}}$
D. ${{\left( \dfrac{2}{3} \right)}^{\dfrac{1}{3}}}$
Answer
491.1k+ views
Hint: We first check if the given P.D.F satisfies the condition of \[\int\limits_{-\infty }^{\infty }{f\left( x \right)dx}=1\]. We take the integration of \[\int\limits_{0}^{1}{3{{x}^{2}}dx}\]. We then use the given condition of $P\left\{ X\le \lambda \right\}=P\left\{ X>\lambda \right\}$ to form the integration part. We solve the equation to find the final solution.
Complete step by step answer:
The given P.D.F is $f\left( x \right)=3{{x}^{2}},0\le x\le 1$. The condition for P.D.F is \[\int\limits_{-\infty }^{\infty }{f\left( x \right)dx}=1\].
Here we take the integration for $0\le x\le 1$.
We get \[\int\limits_{0}^{1}{3{{x}^{2}}dx}=1\].
\[\begin{align}
& \int\limits_{0}^{1}{3{{x}^{2}}dx}=1 \\
& \Rightarrow \left[ {{x}^{3}} \right]_{0}^{1}=1-0=1 \\
\end{align}\]
The given equation satisfies the condition.
It is given that $P\left\{ X\le \lambda \right\}=P\left\{ X>\lambda \right\}$. We express them in the form of integration and get
\[\begin{align}
& P\left\{ X\le \lambda \right\}=P\left\{ X>\lambda \right\} \\
& \Rightarrow \int\limits_{0}^{\lambda }{3{{x}^{2}}dx}=\int\limits_{\lambda }^{1}{3{{x}^{2}}dx} \\
& \Rightarrow \left[ {{x}^{3}} \right]_{0}^{\lambda }=\left[ {{x}^{3}} \right]_{\lambda }^{1} \\
\end{align}\]
We now solve the equation and get
\[\begin{align}
& \left[ {{x}^{3}} \right]_{0}^{\lambda }=\left[ {{x}^{3}} \right]_{\lambda }^{1} \\
& \Rightarrow {{\lambda }^{3}}-0=1-{{\lambda }^{3}} \\
& \Rightarrow 2{{\lambda }^{3}}=1 \\
& \Rightarrow {{\lambda }^{3}}=\dfrac{1}{2} \\
& \Rightarrow \lambda ={{\left( \dfrac{1}{2} \right)}^{\dfrac{1}{3}}} \\
\end{align}\]
Therefore, the correct option is B.
Note: It is a function whose value at any given sample in the sample space can be interpreted as providing a relative likelihood that the value of the random variable would equal that sample. For cases of P.M.F we have to use the distinct values of the masses.
Complete step by step answer:
The given P.D.F is $f\left( x \right)=3{{x}^{2}},0\le x\le 1$. The condition for P.D.F is \[\int\limits_{-\infty }^{\infty }{f\left( x \right)dx}=1\].
Here we take the integration for $0\le x\le 1$.
We get \[\int\limits_{0}^{1}{3{{x}^{2}}dx}=1\].
\[\begin{align}
& \int\limits_{0}^{1}{3{{x}^{2}}dx}=1 \\
& \Rightarrow \left[ {{x}^{3}} \right]_{0}^{1}=1-0=1 \\
\end{align}\]
The given equation satisfies the condition.
It is given that $P\left\{ X\le \lambda \right\}=P\left\{ X>\lambda \right\}$. We express them in the form of integration and get
\[\begin{align}
& P\left\{ X\le \lambda \right\}=P\left\{ X>\lambda \right\} \\
& \Rightarrow \int\limits_{0}^{\lambda }{3{{x}^{2}}dx}=\int\limits_{\lambda }^{1}{3{{x}^{2}}dx} \\
& \Rightarrow \left[ {{x}^{3}} \right]_{0}^{\lambda }=\left[ {{x}^{3}} \right]_{\lambda }^{1} \\
\end{align}\]
We now solve the equation and get
\[\begin{align}
& \left[ {{x}^{3}} \right]_{0}^{\lambda }=\left[ {{x}^{3}} \right]_{\lambda }^{1} \\
& \Rightarrow {{\lambda }^{3}}-0=1-{{\lambda }^{3}} \\
& \Rightarrow 2{{\lambda }^{3}}=1 \\
& \Rightarrow {{\lambda }^{3}}=\dfrac{1}{2} \\
& \Rightarrow \lambda ={{\left( \dfrac{1}{2} \right)}^{\dfrac{1}{3}}} \\
\end{align}\]
Therefore, the correct option is B.
Note: It is a function whose value at any given sample in the sample space can be interpreted as providing a relative likelihood that the value of the random variable would equal that sample. For cases of P.M.F we have to use the distinct values of the masses.
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