The probability function f ( x ) = { 3 x 2 , 0 < x < 1 0 , otherwise f(x)=\begin{cases}
3x^2,\ \ \ 0<x<1
\\0, \ \ \text{otherwise}
\end{cases} f ( x ) = { 3 x 2 , 0 < x < 1 0 , otherwise
a. The CDF of X: F ( x ) = P ( X ≤ x ) = ∫ − ∞ x f ( t ) d t F(x)=P(X\leq x)=\int\limits _{-\infin}^x f(t)dt F ( x ) = P ( X ≤ x ) = − ∞ ∫ x f ( t ) d t
If x ≤ 0 : x\leq 0: x ≤ 0 : F ( x ) = ∫ − ∞ x 0 d t = 0 F(x)= \int\limits _{-\infin}^x 0dt =0 F ( x ) = − ∞ ∫ x 0 d t = 0
If 0 < x < 1 0<x<1 0 < x < 1 : F ( x ) = ∫ 0 x 3 t 2 d t = t 3 ∣ 0 x = x 3 F(x)= \int\limits _{0}^x 3t^2dt =t^3\big|^x_0=x^3 F ( x ) = 0 ∫ x 3 t 2 d t = t 3 ∣ ∣ 0 x = x 3
If 1 ≤ x 1\leq x 1 ≤ x : F ( x ) = ∫ 0 1 3 t 2 d t = t 3 ∣ 0 1 = 1 F(x)= \int\limits _{0}^1 3t^2dt =t^3\big|^1_0=1 F ( x ) = 0 ∫ 1 3 t 2 d t = t 3 ∣ ∣ 0 1 = 1
F ( x ) = { 0 , x ≤ 0 x 3 , 0 < x < 1 1 , 1 ≤ x F(x)=\begin{cases}
0,\ \ x\leq 0
\\
x^3,\ \ 0<x<1
\\
1,\ \ 1\leq x
\end{cases} F ( x ) = ⎩ ⎨ ⎧ 0 , x ≤ 0 x 3 , 0 < x < 1 1 , 1 ≤ x
b. P ( X < 0.5 ) = F ( 0.5 ) = ( 0.5 ) 3 = 0.125 P(X<0.5)= F(0.5)=(0.5)^3=0.125 P ( X < 0.5 ) = F ( 0.5 ) = ( 0.5 ) 3 = 0.125
c. E ( x ) = ∫ − ∞ + ∞ x f ( x ) d x = ∫ 0 1 3 x 3 d x = 3 4 x 4 ∣ 0 1 = 3 4 E(x)=\int\limits _{-\infin}^{+\infin}xf(x)dx=\int\limits _0^1 3x^3dx=\frac{3}{4}x^4\big|^1_0=\frac{3}{4} E ( x ) = − ∞ ∫ + ∞ x f ( x ) d x = 0 ∫ 1 3 x 3 d x = 4 3 x 4 ∣ ∣ 0 1 = 4 3
Answer:
a. F ( x ) = { 0 , x ≤ 0 x 3 , 0 < x < 1 1 , 1 ≤ x F(x)=\begin{cases}
0,\ \ x\leq 0
\\
x^3,\ \ 0<x<1
\\
1,\ \ 1\leq x
\end{cases} F ( x ) = ⎩ ⎨ ⎧ 0 , x ≤ 0 x 3 , 0 < x < 1 1 , 1 ≤ x
b. P ( X < 0.5 ) = 0.125 P(X<0.5)=0.125 P ( X < 0.5 ) = 0.125
c. E ( x ) = 3 4 E(x)=\frac{3}{4} E ( x ) = 4 3
Comments