Solving Problems with Normal and Log-Normal Distributions, Exercises of Engineering Dynamics

Solutions to two examples involving normal and log-normal distributions. The first example calculates the value of x given that 95% of the values in a sample are non-zero and follow a normal distribution. The second example estimates the probability of a log-normally distributed peak exceeding 125 units using frequency analysis.

Typology: Exercises

2012/2013

Uploaded on 03/28/2013

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Example Problem 1
If in a sample there are 95% non-zero values, calculate X .
10
[ ]
[ ]
σ
= ≤≠
=
= = × +=
*
*
*
F (x) . P X x | X
If F ( x )
F (x) . P Z z
x
or . or . .
10
2
0 895 0
0 895
1 255 1 255 15 10 28 33
Tt
= given x 0
follows a normal distribution N (10,15 ) given
=
Get z value corresponding to 0.895 z = 1.255
x
x units
[ ] [ ]
Solution:
== ≥==
=−=⇒ = + *
k . PX , PX x .
F(x ) . . . . . F (x )
10
10 10
1
0 95 0 0 1
10
1 01 09 09 1 095 095
Module 8
Docsity.com
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Example Problem 1

If in a sample there are 95% non-zero values, calculate X 10.

[ ]

[ ]

σ

= ≤ ≠ ≠

= ≤ ∴ − (^) = = × + =

F ( x ). P X x | X If F ( x ) F ( x ). P Z z

or x. or..

10 2

0 895 0

0 895

T 1 255 (^) t 1 255 15 10 28 33

= given x 0 follows a normal distribution N (10,15 ) given = Get z value corresponding to 0.895 z = 1. x (^) x units

[ ] [ ]

Solution: = = ≠ ≥ = = = − = ⇒ = − + *

k. P X , P X x. F( x )..... F ( x )

10 10 10

1 0 1 0 9 0 9 1 0 9 5^10 0 9 5

Docsity.com Module 8

Peak flow data are available for 75 yrs, 20 of the values are zero and the remaining 55 values have a mean of 100 units and std. deviation of 35.1 units and are log normally distributed. Estimate the probability of the peak exceeding 125 units using frequency analysis.

Example Problem 2

[ ]

[ ]

( )

(^55 ) (^75 125 1 1 125 ) 125 125 0

1

= = ≠ > = = − = − + = ≤ ≠

= +

T T

P[X 0]

log-normally distributed

table, frequency table For normal dist. it is K = S X For l

  • (^) T *

T

T V

k. P X F( ) F( x ) k kF ( x ) F ( X ) F ( ) P X X K

X K C og-normal dist. Docsity.com Module 8