Stochastic Modelling and Geostatistics - PowerPoint PPT Presentation

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Stochastic Modelling and Geostatistics

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Lecture (3) Description of Central Tendency Hydrological Records Population vs. Sample Notation Different Types of Means or Averages Arithmetic Mean The Short Cut ... – PowerPoint PPT presentation

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Title: Stochastic Modelling and Geostatistics


1
Lecture (3)
Description of Central Tendency
2
Hydrological Records
3
Population vs. Sample Notation
Population Vs Sample
World People Arabs
Infinite Record (i.e. very long) selected year
4
Different Types of Means or Averages
Arithmetic Geometric Harmonic Quadratic Conside
r a sample of n observations, X1, X2, , Xi, ,
Xn which can be grouped into k classes with
class marks x1,x2,, xi,, xk with corresponding
absolute frequencies, f1,f2,,fi,,fk.
 
5
Arithmetic Mean
X
X1
Xn
Xi
X2
t
 
6
The Short Cut Method
Assume the mean is ltxgtxj Calculate the deviation
from the assumed mean, (xi-xj)
 
7
Geometric Mean
8
Geometric Mean (cont.)
9
Harmonic Mean
10
Quadratic Mean (Mean Square Value)
X
X1
Xn
Xi
X2
t
11
General Formula
12
Applications and Limitations
13
Applications and Limitations (Cont.)
14
Applications and Limitations (Cont.)
Flow parallel to the layers
Flow perpendicular to the layers
15
Applications and Limitations (Cont.)
Quadratic mean describes dispersion, spread or
scatter around the mean, and is known as the
standard deviation from the mean.
16
Median
  • Any value M for which at least 50 of all
    observations are at or above M and at least 50
    are at or below M.

17
Median Estimation
  • Order all observations from smallest to largest.
  • If the number of observations is odd, it is the
    middle object, namely the (n1)/2th
    observation.
  • For n 61, it is the 31st
  • If the number of observations is even then, to
    get a unique value, take the average of the
    (n/2)th and the (n/2 1)th observation.
  • For 60, it is the average of the 30th and the
    31st observation.

18
The median has nice properties
  • Easy to understand
  • (½ data above, ½ data below)
  • Resistant measure of central tendency (location)
    not affected by extreme (unusual) observations.

19
Percentiles and Quartiles
In the cumulative distribution diagram, the range
is from 0 to 100. If this range is divided into
a hundred equal parts. The projection of these
parts on the x-axis are percentiles and denoted
by, X_0.01, X_0.02,, X_0.99.
20
Percentiles, Quartiles and Median (Cont.)
The 25th and 75th percentiles correspond to the
first and third quartiles. Median (Xm) it is
the second quartile, X_0.50, divides the set of
observations into two numerically equal
groups. Median geometrically is the value that
divides the frequency histogram into two parts
having equal areas.
21
Graphical Representation
X_0.50
X_0.75
X_0.25
22
Mode
The mode is the variate that corresponds to the
largest ordinate of a frequency curve.
Frequency distributions can be described
as Uni-modal, bi-model, multi-model if it has
one, two or more modes.
23
Mode in a Histogram
  1. Mode(s)
  2. Median
  3. Mean

24
Four Rules of Summation
n
25
Four Rules of Summation
26
Four Rules of Summation
27
Four Rules of Summation
28
Excel Application
  • See Excel

29
Mean, Median, Mode
  • Use AVERAGE or AVERAGEA to calculate the
    arithmetic mean
  • Cell AVERAGE(number1, number2, etc.)
  • Use MEDIAN to return the middle number
  • Cell MEDIAN(number1, number2, etc)
  • Use MODE to return the most common value
  • Cell MODE(number1, number2, etc)

30
Geometric Mean
  • Use GEOMEAN to calculate the geometric mean
  • Cell GEOMEAN (number1, number2, etc.)

31
Percentiles and Quartiles
  • Use PERCENTILE to return the kth percentile of a
    data set
  • Cell PERCENTILE(array, percentile)
  • Percentile argument is a value between 0 and 1
  • Use QUARTILE to return the given quartile of a
    data set
  • Cell QUARTILE(array, quart)
  • Quart is 1, 2, 3 or 4
  • IQR Q3-Q1
  • May return different values to statistical package
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