Transcript Document

© Dr. Akm Saiful Islam WFM-6204: Hydrologic Statistics

Lecture-3: Probabilistic analysis: (Part-2)

Akm Saiful Islam

Institute of Water and Flood Management (IWFM) Bangladesh University of Engineering and Technology (BUET) December, 2006

WFM 6204: Hydrologic Statistics © Dr. Akm Saiful Islam

Probability Distributions and Their Applications

 Continuous Distributions  Normal distribution  Lognormal distribution  Gamma distribution  Pearson Type III distribution  Gumbel’s Extremal distribution

WFM 6204: Hydrologic Statistics © Dr. Akm Saiful Islam

Normal Distribution

The probability that X is less than or equal to x when X can prob (

X

x

) 

p x

(

x

)    

x

( 2  2 )  1 / 2

e

 (

t

  ) 2 / 2  2

dt

(4.9)  2 The parameters (mean) and (variance) are denoted as location and scale parameters, respectively. The normal distribution is a bell-shaped, continuous and symmetrical distribution (the coefficient of skew is zero).

WFM 6204: Hydrologic Statistics © Dr. Akm Saiful Islam   2 If is held constant and varied, the distribution changes as in Figure 4.2.1.1.

Figure 4.2.1.1

Normal distributions with same mean and different variances

WFM 6204: Hydrologic Statistics © Dr. Akm Saiful Islam   2  not change scale but docs change location as in Figure 4.2.1.2. A common notation for indicating that a random variable is normally distributed with mean and (  ,  2 )

Figure 4.2.1.2

Normal distributions with same variance and different means

WFM 6204: Hydrologic Statistics © Dr. Akm Saiful Islam  If a random variable is N and Y= a + bX , the distribution of Y can be shown to be . 2  2 ) This can be proven using the method of derived distributions. Furthermore, if for , are

i

, 2 , 

n

independently and normally distributed with 

i

i

2 is normally distributed with

Y

a

b

1

X

1 

b

2

X

2   

b n X n

Y

a

 

n i

 1

b i

i

Y

2  

n i

 1

b i

2 

i

2 (4.7) and (4.8)  Any linear function of independent normal random variables is also a normal random variable.

WFM 6204: Hydrologic Statistics © Dr. Akm Saiful Islam

Standard normal distribution

 The probability that X is less than or equal from prob (

X

x

) 

p x

(

x

)    

x

( 2  2 )  1 / 2

e

 (

t

  ) 2 / 2  2

dt

(4.9)

WFM 6204: Hydrologic Statistics © Dr. Akm Saiful Islam  The equation (4.9) cannot be evaluated analytically so that approximate methods of integration arc required. If a tabulation of the integral was made, a separate table would be required for each value of and . By using the liner transformation , the random variable Z will be N(0,1). The random variable Z is said to be standardized (has and ) and N(0,1) is said to be the standard normal distribution. The standard normal distribution is given by

p Z

(

z

)  ( 2  )  1 / 2

e

z

2 / 2   

z

  (4.10) and the cumulative standard normal is given by prob(

Z

z

) 

P Z

(

z

)   

z

 ( 2  )  1 / 2

e

t

2 / 2

dt

(4.11)

WFM 6204: Hydrologic Statistics © Dr. Akm Saiful Islam

Figure 4.2.1.3

Standard normal distribution

WFM 6204: Hydrologic Statistics © Dr. Akm Saiful Islam     Figure 4.2.1.3 shows the standard normal distribution which along with the transformation

Z

 (

X

  ) /  contains all of the information shown in Figures 4.1 and 4.2.

p Z

( tabulated.

Z

)

P Z

(

z

Most tables utilize the symmetry of the normal distribution so that only positive values of Z are shown. Tables of prob ( 0 

Z P Z

(

z

) 

z

)  Care must be exercised when using normal probability tables to see what values are tabulated.

WFM 6204: Hydrologic Statistics © Dr. Akm Saiful Islam 

Example-1:

As an example of using tables of the normal distribution consider a sample drawn from a N(15,25). What is the prob(15.6

≤ X≤ 20.4)? [Hann]  Solution:

WFM 6204: Hydrologic Statistics © Dr. Akm Saiful Islam 

Example-2:

What is the prob(10.5

≤ X≤ 20.4) if X distributed N(15,25)? [Hann]  Solution:

WFM 6204: Hydrologic Statistics © Dr. Akm Saiful Islam 

Example-3: Assume the following data follows a normal distribution. Find the rain depth that would have a recurrence interval of 100 years.

    Year 2000 1999 1998 Annual Rainfall (in) 43 44 38  1997 31   1996 47 ….. …..

WFM 6204: Hydrologic Statistics © Dr. Akm Saiful Islam Solution: Mean = 41.5, St. Dev = 6.7 in (given) x= Mean + Std.Dev * z x = 41.5 + z(6.7) P(z) = 1/T = 1/100 = 0.01

F(z) = 0.5 – P(z) = 0.49

From Interpolation using Tables E.4

Z = 2.236

X = 41.5 + (2.326 x 6.7) = 57.1 in

WFM 6204: Hydrologic Statistics © Dr. Akm Saiful Islam

Properties of common distributions

Bi-Nominal Distribution

PDF Range Mean

P

(

x

) 

x

!

(

n n

!

x

)!

p x

( 1 

p

)

n

x

0 

x

n np

Variance

np

( 1 

p

)

WFM 6204: Hydrologic Statistics © Dr. Akm Saiful Islam

Properties of common distributions

Poisson Distribution

PDF

P

(

x

)  

x e

 

x

!

Range Mean Variance 0 

x

 ...

 

WFM 6204: Hydrologic Statistics © Dr. Akm Saiful Islam

Properties of common distributions

Normal Distribution

PDF

f

(

x

)   1 2 

e

 (

x

  ) 2 / 2  2 Range Mean Variance  

x

   2

WFM 6204: Hydrologic Statistics © Dr. Akm Saiful Islam

Properties of common distributions

Log-Normal Distribution ( y = ln x)

PDF

f

(

y

)  

x

1 2 

e

 (

y

  ) 2 / 2  2 Range Mean Variance  

y

 

y

y

2

WFM 6204: Hydrologic Statistics © Dr. Akm Saiful Islam

Properties of common distributions

Gamma Distribution

PDF Range Mean Variance

WFM 6204: Hydrologic Statistics © Dr. Akm Saiful Islam

Properties of common distributions

Gumbel Distribution

PDF Range Mean Variance

WFM 6204: Hydrologic Statistics © Dr. Akm Saiful Islam

Properties of common distributions

Extreme Value Type-1 Distribution

PDF Range Mean Variance

WFM 6204: Hydrologic Statistics © Dr. Akm Saiful Islam

Properties of common distributions

Log-Pearson III Distribution

PDF Range Mean Variance

WFM 6204: Hydrologic Statistics © Dr. Akm Saiful Islam

Assignment-1

 The total annual runoff from a small drainage basin is determined to be approximately normal with a mean of 14.0

inch and a variance of 9.0

inch 2 .

Determine the probability that the annual runoff form the basin will be less than 11.0

inch in all three consecutive years.

of next the three