Cumulative distribution function of normal distribution is
F ( x ) = 1 2 ( 1 + e r f ( x − μ 2 σ ) ) F\left( x \right) = \frac{1}{2}\left(1 + \mathop{\mathrm{erf}}\nolimits \left(\frac{x-\mu}{\sqrt{2}\sigma}\right) \right) F ( x ) = 2 1 ( 1 + erf ( 2 σ x − μ ) )
Here μ = 144.5 , σ = 36 \mu = 144.5, \sigma = 36 μ = 144.5 , σ = 36 , so
F ( x ) = 1 2 ( 1 + e r f ( x − 144.5 36 2 ) ) F\left( x \right) = \frac{1}{2}\left(1 + \mathop{\mathrm{erf}}\nolimits \left(\frac{x-144.5}{36\sqrt{2}}\right) \right) F ( x ) = 2 1 ( 1 + erf ( 36 2 x − 144.5 ) ) ,
where erf function is
e r f ( x ) = 2 π ∫ 0 x e − t 2 d t \mathop{\mathrm{erf}}\nolimits\left(x\right) = \frac{2}{\sqrt{\pi}} \int\limits_0^x e^{-t^2} dt erf ( x ) = π 2 0 ∫ x e − t 2 d t .
To find a value of erf function, we have to check a special table of values or just use a calculator.
Solution:
P ( X < 130 ) = F ( 130 ) = 1 2 ( 1 + e r f ( − 14.5 36 2 ) ) ≈ 1 2 ( 1 − 0.3129 ) = 0.34355 P\left(X < 130\right) = F\left( 130 \right) = \frac{1}{2} \left( 1 + \mathop{\mathrm{erf}}\nolimits \left( \frac{-14.5}{36\sqrt{2}} \right) \right) \approx \frac{1}{2} \left( 1 - 0.3129 \right) = 0.34355\\[0.3cm] P ( X < 130 ) = F ( 130 ) = 2 1 ( 1 + erf ( 36 2 − 14.5 ) ) ≈ 2 1 ( 1 − 0.3129 ) = 0.34355
Answer: 0.34355
Solution:
P ( 151.5 < X < 182 ) = F ( 182 ) − F ( 151.5 ) = P\left( 151.5 < X < 182 \right) = F\left( 182 \right) - F\left( 151.5 \right) = \\[0.3cm] P ( 151.5 < X < 182 ) = F ( 182 ) − F ( 151.5 ) =
= 1 2 ( 1 + e r f ( 37.5 36 2 ) ) − 1 2 ( 1 + e r f ( 7 36 2 ) ) ≈ \quad = \frac{1}{2} \left( 1 + \mathop{\mathrm{erf}}\nolimits \left( \frac{37.5}{36\sqrt{2}} \right) \right)
- \frac{1}{2} \left( 1 + \mathop{\mathrm{erf}}\nolimits \left( \frac{7}{36\sqrt{2}} \right) \right) \approx \\[0.3cm] = 2 1 ( 1 + erf ( 36 2 37.5 ) ) − 2 1 ( 1 + erf ( 36 2 7 ) ) ≈
≈ 1 2 ( 1 + 0.7024 ) − 1 2 ( 1 + 0.1542 ) ≈ 0.274 \quad \approx \frac{1}{2} \left( 1 + 0.7024 \right) - \frac{1}{2} \left( 1 + 0.1542 \right) \approx 0.274 \\[0.3cm] ≈ 2 1 ( 1 + 0.7024 ) − 2 1 ( 1 + 0.1542 ) ≈ 0.274
Answer: 0.274
Solution:
P ( X ≥ 150 ) = 1 − F ( 150 ) = 1 − 1 2 ( 1 + e r f ( 5.5 36 2 ) ) ≈ P\left( X \geq 150 \right) = 1 - F\left( 150 \right) = 1 - \frac{1}{2}\left( 1 + \mathop{\mathrm{erf}}\nolimits \left( \frac{5.5}{36\sqrt{2}} \right) \right) \approx \\[0.3cm] P ( X ≥ 150 ) = 1 − F ( 150 ) = 1 − 2 1 ( 1 + erf ( 36 2 5.5 ) ) ≈
≈ 1 − 1 2 ( 1 + 0.1214 ) ≈ 0.4393 \quad \approx 1-\frac{1}{2}\left( 1 + 0.1214 \right) \approx 0.4393 \\[0.3cm] ≈ 1 − 2 1 ( 1 + 0.1214 ) ≈ 0.4393
Answer: 0.4393
Solution:
P ( X > x o ) = 1 − F ( x o ) = 1 − 1 2 ( 1 + e r f ( x o − 144.5 36 2 ) ) = 0.6 P\left( X > x_o \right) = 1 - F\left( x_o \right) = 1 - \frac{1}{2}\left( 1 + \mathop{\mathrm{erf}}\nolimits \left( \frac{x_o - 144.5}{36\sqrt{2}} \right) \right) = 0.6 \\[0.3cm] P ( X > x o ) = 1 − F ( x o ) = 1 − 2 1 ( 1 + erf ( 36 2 x o − 144.5 ) ) = 0.6
⟹ e r f ( x o − 144.5 36 2 ) = − 0.2 \Longrightarrow \quad \mathop{\mathrm{erf}}\nolimits \left( \frac{x_o - 144.5}{36\sqrt{2}} \right) = -0.2 \\[0.3cm] ⟹ erf ( 36 2 x o − 144.5 ) = − 0.2
⟹ x o − 144.5 36 2 ≈ − 0.1791 \Longrightarrow \quad \frac{x_o - 144.5}{36\sqrt{2}} \approx -0.1791 \\[0.3cm] ⟹ 36 2 x o − 144.5 ≈ − 0.1791
⟹ x o ≈ 135.382 ≈ 135.5 \Longrightarrow \quad x_o \approx 135.382 \approx 135.5\\[0.3cm] ⟹ x o ≈ 135.382 ≈ 135.5
Answer: 135.5
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